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The rapid advancement of large language models (LLMs) has revolutionized artificial intelligence, introducing unprecedented capabilities in natural language processing and multimodal content generation.
Risks from Learned Optimization in Advanced Machine Learning Systems
Evan Hubinger, Chris van Merwijk, Vladimir Mikulik, Joar Skalse, and Scott Garrabrant. 2019 · 1906
Earlier work this paper cites.
On the Privacy Preserving Properties of Random Data Perturbation Techniques. In Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM 2003), 19-22 December 2003, Melbourne, Florida, USA . IEEE Computer Society, 99–106
Hillol Kargupta, Souptik Datta, Qi Wang, and Krishnamoorthy Sivakumar. 2003 · 2003
Earlier work this paper cites.
Threats to Federated Learning: A Survey
Lingjuan Lyu, Han Yu, and Qiang Yang. 2020 · 2003
Earlier work this paper cites.
Trojan Detection using IC Fingerprinting. In 2007 IEEE Symposium on Security and Privacy (S&P 2007), 20-23 May 2007, Oakland, California, USA . IEEE Computer Society, 296–310
Dakshi Agrawal, Selçuk Baktir, Deniz Karakoyunlu, Pankaj Rohatgi, and Berk Sunar. 2007 · 2007
Earlier work this paper cites.
Hardware Trojan Detection Using Path Delay Fingerprint. In IEEE International Workshop on Hardware-Oriented Security and Trust, HOST 2008, Anaheim, CA, USA, June 9, 2008. Proceedings , Mohammad Tehranipoor and Jim Plusquellic (Eds.). IEEE Computer Society, 51–57
Yier Jin and Yiorgos Makris. 2008 · 2008
Earlier work this paper cites.
MERO: A Statistical Approach for Hardware Trojan Detection. In Cryptographic Hardware and Embedded Systems - CHES 2009, 11th International Workshop, Lausanne, Switzerland, September 6-9, 2009, Proceedings (Lecture Notes in Computer Science, Vol. 5747) , Christophe Clavier and Kris Gaj (Eds.). Springer, 396–410
Rajat Subhra Chakraborty, Francis G. Wolff, Somnath Paul, Christos A. Papachristou, and Swarup Bhunia. 2009 · 2009
Earlier work this paper cites.
Automated software license analysis
Timo Tuunanen, Jussi Koskinen, and Tommi Kärkkäinen. 2009 · 2009
Earlier work this paper cites.
A sentence-matching method for automatic license identification of source code files. In ASE 2010, 25th IEEE/ACM International Conference on Automated Software Engineering, Antwerp, Belgium, September 20-24, 2010 , Charles Pecheur, Jamie Andrews, and Elisabetta Di Nitto (Eds.). ACM, 437–446
Daniel M. Germán, Yuki Manabe, and Katsuro Inoue. 2010 · 2010
Earlier work this paper cites.
An exploratory study of the evolution of software licensing. In Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1, ICSE 2010, Cape Town, South Africa, 1-8 May 2010 , Jeff Kramer, Judith Bishop, Premkumar T. Devanbu, and Sebastián Uchitel (Eds.). ACM, 145–154
Massimiliano Di Penta, Daniel M. Germán, Yann-Gaël Guéhéneuc, and Giuliano Antoniol. 2010 · 2010
Earlier work this paper cites.
Layout-Aware Switching Activity Localization to Enhance Hardware Trojan Detection
Hassan Salmani and Mohammad Tehranipoor. 2012 · 2011
Earlier work this paper cites.
Why people hate your app: making sense of user feedback in a mobile app store. In The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013, Chicago, IL, USA, August 11-14, 2013 , Inderjit S. Dhillon, Yehuda Koren, Rayid Ghani, Ted E. Senator, Paul Bradley, Rajesh Parekh, Jingrui He, Robert L. Grossman, and Ramasamy Uthurusamy (Eds.). ACM, 1276–1284
Bin Fu, Jialiu Lin, Lei Li, Christos Faloutsos, Jason I. Hong, and Norman M. Sadeh. 2013 · 2013
Earlier work this paper cites.
Determinants of Mobile Apps’ Success: Evidence from the App Store Market
Gunwoong Lee and T. S. Raghu. 2014 · 2014
Earlier work this paper cites.
Tracing software build processes to uncover license compliance inconsistencies. In ACM/IEEE International Conference on Automated Software Engineering, ASE ’14, Vasteras, Sweden - September 15 - 19, 2014 , Ivica Crnkovic, Marsha Chechik, and Paul Grünbacher (Eds.). ACM, 731–742
Sander van der Burg, Eelco Dolstra, Shane McIntosh, Julius Davies, Daniel M. Germán, and Armijn Hemel. 2014 · 2014
Earlier work this paper cites.
A Large Scale Study of License Usage on GitHub. In 37th IEEE/ACM International Conference on Software Engineering, ICSE 2015, Florence, Italy, May 16-24, 2015, Volume 2 , Antonia Bertolino, Gerardo Canfora, and Sebastian G. Elbaum (Eds.). IEEE Computer Society, 772–774
Christopher Vendome. 2015 · 2015
Earlier work this paper cites.
License usage and changes: a large-scale study of Java projects on GitHub. In Proceedings of the 2015 IEEE 23rd International Conference on Program Comprehension, ICPC 2015, Florence/Firenze, Italy, May 16-24, 2015 , Andrea De Lucia, Christian Bird, and Rocco Oliveto (Eds.). IEEE Computer Society, 218–228
Christopher Vendome, Mario Linares Vásquez, Gabriele Bavota, Massimiliano Di Penta, Daniel M. Germán, and Denys Poshyvanyk. 2015 · 2015
Earlier work this paper cites.
Big data provenance: Challenges, state of the art and opportunities. In 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29 - November 1, 2015 . IEEE Computer Society, 2509–2516
Jianwu Wang, Daniel Crawl, Shweta Purawat, Mai H. Nguyen, and Ilkay Altintas. 2015 · 2015
Earlier work this paper cites.
A Survey of App Store Analysis for Software Engineering
William J. Martin, Federica Sarro, Yue Jia, Yuanyuan Zhang, and Mark Harman. 2017 · 2016
Earlier work this paper cites.
Assisting developers with license compliance. In Proceedings of the 38th International Conference on Software Engineering, ICSE 2016, Austin, TX, USA, May 14-22, 2016 - Companion Volume , Laura K. Dillon, Willem Visser, and Laurie A. Williams (Eds.). ACM, 811–814
Christopher Vendome and Denys Poshyvanyk. 2016 · 2016
Earlier work this paper cites.
A2: Analog Malicious Hardware. In IEEE Symposium on Security and Privacy, SP 2016, San Jose, CA, USA, May 22-26, 2016 . IEEE Computer Society, 18–37
Kaiyuan Yang, Matthew Hicks, Qing Dong, Todd M. Austin, and Dennis Sylvester. 2016 · 2016
Earlier work this paper cites.
Hardware Trojan Detection Through Chip-Free Electromagnetic Side-Channel Statistical Analysis
Jiaji He, Yiqiang Zhao, Xiaolong Guo, and Yier Jin. 2017 · 2017
Earlier work this paper cites.
License usage and changes: a large-scale study on gitHub
Christopher Vendome, Gabriele Bavota, Massimiliano Di Penta, Mario Linares Vásquez, Daniel M. Germán, and Denys Poshyvanyk. 2017a · 2017
Earlier work this paper cites.
Machine learning-based detection of open source license exceptions. In Proceedings of the 39th International Conference on Software Engineering, ICSE 2017, Buenos Aires, Argentina, May 20-28, 2017 , Sebastián Uchitel, Alessandro Orso, and Martin P. Robillard (Eds.). IEEE / ACM, 118–129
Christopher Vendome, Mario Linares Vásquez, Gabriele Bavota, Massimiliano Di Penta, Daniel M. Germán, and Denys Poshyvanyk. 2017b · 2017
Earlier work this paper cites.
Analysis of license inconsistency in large collections of open source projects
Yuhao Wu, Yuki Manabe, Tetsuya Kanda, Daniel M. Germán, and Katsuro Inoue. 2017 · 2017
Earlier work this paper cites.
Understanding The Security of Discrete GPUs. In Proceedings of the General Purpose GPUs, GPGPU at PPoPP, Austin, TX, USA, February 4-8, 2017 . ACM, 1–11
Zhiting Zhu, Sangman Kim, Yuri Rozhanski, Yige Hu, Emmett Witchel, and Mark Silberstein. 2017 · 2017
Earlier work this paper cites.
Software ecosystem call graph for dependency management. In Proceedings of the 40th International Conference on Software Engineering: New Ideas and Emerging Results, ICSE (NIER) 2018, Gothenburg, Sweden, May 27 - June 03, 2018 , Andrea Zisman and Sven Apel (Eds.). ACM, 101–104
Joseph Hejderup, Arie van Deursen, and Georgios Gousios. 2018 · 2018
Earlier work this paper cites.
Constructing supply chains in open source software. In Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings, ICSE 2018, Gothenburg, Sweden, May 27 - June 03, 2018 , Michel Chaudron, Ivica Crnkovic, Marsha Chechik, and Mark Harman (Eds.). ACM, 458–459
Yuxing Ma. 2018 · 2018
Earlier work this paper cites.
Rendered Insecure: GPU Side Channel Attacks are Practical. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, CCS 2018, Toronto, ON, Canada, October 15-19, 2018 , David Lie, Mohammad Mannan, Michael Backes, and XiaoFeng Wang (Eds.). ACM, 2139–2153
Hoda Naghibijouybari, Ajaya Neupane, Zhiyun Qian, and Nael B. Abu-Ghazaleh. 2018 · 2018
Earlier work this paper cites.
Reducing Gender Bias in Abusive Language Detection. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31 - November 4, 2018 , Ellen Riloff, David Chiang, Julia Hockenmaier, and Jun’ichi Tsujii (Eds.). Association for Computational Linguistics, 2799–2804
Ji Ho Park, Jamin Shin, and Pascale Fung. 2018 · 2018
Earlier work this paper cites.
Applying Chaos Theory for Runtime Hardware Trojan Monitoring and Detection
Hong Zhao, Luke Kwiat, Kevin A. Kwiat, Charles A. Kamhoua, and Laurent Njilla. 2020 · 2018
Earlier work this paper cites.
Data Validation for Machine Learning. In Proceedings of the Second Conference on Machine Learning and Systems, SysML 2019, Stanford, CA, USA, March 31 - April 2, 2019 , Ameet Talwalkar, Virginia Smith, and Matei Zaharia (Eds.). mlsys.org
Eric Breck, Neoklis Polyzotis, Sudip Roy, Steven Whang, and Martin Zinkevich. 2019 · 2019
Earlier work this paper cites.
Differential Privacy Techniques for Cyber Physical Systems: A Survey
Muneeb Ul Hassan, Mubashir Husain Rehmani, and Jinjun Chen. 2020 · 2019
Earlier work this paper cites.
SAC: A System for Big Data Lineage Tracking. In 35th IEEE International Conference on Data Engineering, ICDE 2019, Macao, China, April 8-11, 2019 . IEEE, 1964–1967
MingJie Tang, Saisai Shao, Weiqing Yang, Yanbo Liang, Yongyang Yu, Bikas Saha, and Dongjoon Hyun. 2019 · 2019
Earlier work this paper cites.
RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models. In Findings of the Association for Computational Linguistics: EMNLP 2020, Online Event, 16-20 November 2020 (Findings of ACL, Vol. EMNLP 2020) , Trevor Cohn, Yulan He, and Yang Liu (Eds.). Association for Computational Linguistics, 3356–3369
Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi, and Noah A. Smith. 2020 · 2020
Earlier work this paper cites.
Survey of Software Supply Chain Security
Xixun He, Yuqing Zhang, and Qixu Liu. 2020 · 2020
Earlier work this paper cites.
Overview and Importance of Data Quality for Machine Learning Tasks. In KDD ’20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, CA, USA, August 23-27, 2020 , Rajesh Gupta, Yan Liu, Jiliang Tang, and B. Aditya Prakash (Eds.). ACM, 3561–3562
Abhinav Jain, Hima Patel, Lokesh Nagalapatti, Nitin Gupta, Sameep Mehta, Shanmukha C. Guttula, Shashank Mujumdar, Shazia Afzal, Ruhi Sharma Mittal, and Vitobha Munigala. 2020 · 2020
Earlier work this paper cites.
Exploiting Bank Conflict-based Side-channel Timing Leakage of GPUs
Zhen Hang Jiang, Yunsi Fei, and David R. Kaeli. 2020 · 2020
Earlier work this paper cites.
Vamsa: Automated Provenance Tracking in Data Science Scripts. In KDD ’20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, CA, USA, August 23-27, 2020 , Rajesh Gupta, Yan Liu, Jiliang Tang, and B. Aditya Prakash (Eds.). ACM, 1542–1551
Mohammad Hossein Namaki, Avrilia Floratou, Fotis Psallidas, Subru Krishnan, Ashvin Agrawal, Yinghui Wu, Yiwen Zhu, and Markus Weimer. 2020 · 2020
Earlier work this paper cites.
Toxicity Detection: Does Context Really Matter?. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, Online, July 5-10, 2020 , Dan Jurafsky, Joyce Chai, Natalie Schluter, and Joel R. Tetreault (Eds.). Association for Computational Linguistics, 4296–4305
John Pavlopoulos, Jeffrey Sorensen, Lucas Dixon, Nithum Thain, and Ion Androutsopoulos. 2020 · 2020
Earlier work this paper cites.
Improving Reproducibility of Data Science Pipelines through Transparent Provenance Capture
Lukas Rupprecht, James C. Davis, Constantine Arnold, Yaniv Gur, and Deepavali Bhagwat. 2020 · 2020
Earlier work this paper cites.
"Who said it, and Why?" Provenance for Natural Language Claims. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, Online, July 5-10, 2020 , Dan Jurafsky, Joyce Chai, Natalie Schluter, and Joel R. Tetreault (Eds.). Association for Computational Linguistics, 4416–4426
Yi Zhang, Zachary G. Ives, and Dan Roth. 2020 · 2020
Earlier work this paper cites.
Enabling Rack-scale Confidential Computing using Heterogeneous Trusted Execution Environment. In 2020 IEEE Symposium on Security and Privacy, SP 2020, San Francisco, CA, USA, May 18-21, 2020 . IEEE, 1450–1465
Jianping Zhu, Rui Hou, XiaoFeng Wang, Wenhao Wang, Jiangfeng Cao, Boyan Zhao, Zhongpu Wang, Yuhui Zhang, Jiameng Ying, Lixin Zhang, and Dan Meng. 2020 · 2020
Earlier work this paper cites.
Benchmarking Knowledge-Enhanced Commonsense Question Answering via Knowledge-to-Text Transformation. In Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021 . AAAI Press, 12574–12582
Ning Bian, Xianpei Han, Bo Chen, and Le Sun. 2021 · 2021
Earlier work this paper cites.
On the Opportunities and Risks of Foundation Models
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren E. Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, and et al. 2021 · 2021
Earlier work this paper cites.
Extracting Training Data from Large Language Models. In 30th USENIX Security Symposium, USENIX Security 2021, August 11-13, 2021 , Michael D. Bailey and Rachel Greenstadt (Eds.). USENIX Association, 2633–2650
Nicholas Carlini, Florian Tramèr, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom B. Brown, Dawn Song, Úlfar Erlingsson, Alina Oprea, and Colin Raffel. 2021 · 2021
Earlier work this paper cites.
Towards Measuring Supply Chain Attacks on Package Managers for Interpreted Languages. In 28th Annual Network and Distributed System Security Symposium, NDSS 2021, virtually, February 21-25, 2021 . The Internet Society
Ruian Duan, Omar Alrawi, Ranjita Pai Kasturi, Ryan Elder, Brendan Saltaformaggio, and Wenke Lee. 2021 · 2021
Earlier work this paper cites.
Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure. In FAccT ’21: 2021 ACM Conference on Fairness, Accountability, and Transparency, Virtual Event / Toronto, Canada, March 3-10, 2021 , Madeleine Clare Elish, William Isaac, and Richard S. Zemel (Eds.). ACM, 560–575
Ben Hutchinson, Andrew Smart, Alex Hanna, Emily Denton, Christina Greer, Oddur Kjartansson, Parker Barnes, and Margaret Mitchell. 2021 · 2021
Earlier work this paper cites.
Alignment Rationale for Natural Language Inference. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL/IJCNLP 2021, (Volume 1: Long Papers), Virtual Event, August 1-6, 2021 , Chengqing Zong, Fei Xia, Wenjie Li, and Roberto Navigli (Eds.). Association for Computational Linguistics, 5372–5387
Zhongtao Jiang, Yuanzhe Zhang, Zhao Yang, Jun Zhao, and Kang Liu. 2021 · 2021
Earlier work this paper cites.
Bias Out-of-the-Box: An Empirical Analysis of Intersectional Occupational Biases in Popular Generative Language Models. In Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual , Marc’Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, and Jennifer Wortman Vaughan (Eds.). 2611–2624
Hannah Rose Kirk, Yennie Jun, Filippo Volpin, Haider Iqbal, Elias Benussi, Frédéric A. Dreyer, Aleksandar Shtedritski, and Yuki M. Asano. 2021 · 2021
Earlier work this paper cites.
Hidden Backdoors in Human-Centric Language Models. In CCS ’21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15 - 19, 2021 , Yongdae Kim, Jong Kim, Giovanni Vigna, and Elaine Shi (Eds.). ACM, 3123–3140
Shaofeng Li, Hui Liu, Tian Dong, Benjamin Zi Hao Zhao, Minhui Xue, Haojin Zhu, and Jialiang Lu. 2021a · 2021
Earlier work this paper cites.
ModelDiff: testing-based DNN similarity comparison for model reuse detection. In ISSTA ’21: 30th ACM SIGSOFT International Symposium on Software Testing and Analysis, Virtual Event, Denmark, July 11-17, 2021 , Cristian Cadar and Xiangyu Zhang (Eds.). ACM, 139–151
Yuanchun Li, Ziqi Zhang, Bingyan Liu, Ziyue Yang, and Yunxin Liu. 2021b · 2021
Earlier work this paper cites.
Towards Understanding and Mitigating Social Biases in Language Models. In Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event (Proceedings of Machine Learning Research, Vol. 139) , Marina Meila and Tong Zhang (Eds.). PMLR, 6565–6576
Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, and Ruslan Salakhutdinov. 2021 · 2021
Earlier work this paper cites.
Quantifying and alleviating political bias in language models
Ruibo Liu, Chenyan Jia, Jason Wei, Guangxuan Xu, and Soroush Vosoughi. 2022b · 2021
Earlier work this paper cites.
On the Experiences of Adopting Automated Data Validation in an Industrial Machine Learning Project. In 43rd IEEE/ACM International Conference on Software Engineering: Software Engineering in Practice, ICSE (SEIP) 2021, Madrid, Spain, May 25-28, 2021 . IEEE, 248–257
Lucy Ellen Lwakatare, Ellinor Rånge, Ivica Crnkovic, and Jan Bosch. 2021 · 2021
Earlier work this paper cites.
Probing Toxic Content in Large Pre-Trained Language Models. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL/IJCNLP 2021, (Volume 1: Long Papers), Virtual Event, August 1-6, 2021 , Chengqing Zong, Fei Xia, Wenjie Li, and Roberto Navigli (Eds.). Association for Computational Linguistics, 4262–4274
Nedjma Ousidhoum, Xinran Zhao, Tianqing Fang, Yangqiu Song, and Dit-Yan Yeung. 2021 · 2021
Earlier work this paper cites.
Automated Test Generation for Hardware Trojan Detection using Reinforcement Learning. In ASPDAC ’21: 26th Asia and South Pacific Design Automation Conference, Tokyo, Japan, January 18-21, 2021 . ACM, 408–413
Zhixin Pan and Prabhat Mishra. 2021 · 2021
Earlier work this paper cites.
"Everyone wants to do the model work, not the data work": Data Cascades in High-Stakes AI. In CHI ’21: CHI Conference on Human Factors in Computing Systems, Virtual Event / Yokohama, Japan, May 8-13, 2021 , Yoshifumi Kitamura, Aaron Quigley, Katherine Isbister, Takeo Igarashi, Pernille Bjørn, and Steven Mark Drucker (Eds.). ACM, 39:1–39:15
Nithya Sambasivan, Shivani Kapania, Hannah Highfill, Diana Akrong, Praveen K. Paritosh, and Lora Aroyo. 2021 · 2021
Earlier work this paper cites.
Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks. In Proceedings of the 38th International Conference on Machine Learning, ICML 2021, 18-24 July 2021, Virtual Event (Proceedings of Machine Learning Research, Vol. 139) , Marina Meila and Tong Zhang (Eds.). PMLR, 9389–9398
Avi Schwarzschild, Micah Goldblum, Arjun Gupta, John P. Dickerson, and Tom Goldstein. 2021 · 2021
Earlier work this paper cites.
Detecting Hardware Trojans Using Combined Self-Testing and Imaging
Nidish Vashistha, Hangwei Lu, Qihang Shi, Damon L. Woodard, Navid Asadizanjani, and Mark M. Tehranipoor. 2022 · 2021
Earlier work this paper cites.
A Survey on Distributed Machine Learning
Joost Verbraeken, Matthijs Wolting, Jonathan Katzy, Jeroen Kloppenburg, Tim Verbelen, and Jan S. Rellermeyer. 2021 · 2021
Earlier work this paper cites.
Challenges in Detoxifying Language Models. In Findings of the Association for Computational Linguistics: EMNLP 2021, Virtual Event / Punta Cana, Dominican Republic, 16-20 November, 2021 , Marie-Francine Moens, Xuanjing Huang, Lucia Specia, and Scott Wen-tau Yih (Eds.). Association for Computational Linguistics, 2447–2469
Johannes Welbl, Amelia Glaese, Jonathan Uesato, Sumanth Dathathri, John Mellor, Lisa Anne Hendricks, Kirsty Anderson, Pushmeet Kohli, Ben Coppin, and Po-Sen Huang. 2021 · 2021
Earlier work this paper cites.
Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities. In SIGMOD ’21: International Conference on Management of Data, Virtual Event, China, June 20-25, 2021 , Guoliang Li, Zhanhuai Li, Stratos Idreos, and Divesh Srivastava (Eds.). ACM, 2639–2652
Doris Xin, Hui Miao, Aditya G. Parameswaran, and Neoklis Polyzotis. 2021 · 2021
Earlier work this paper cites.
Your fairness may vary: Pretrained language model fairness in toxic text classification. In Findings of the Association for Computational Linguistics: ACL 2022, Dublin, Ireland, May 22-27, 2022 , Smaranda Muresan, Preslav Nakov, and Aline Villavicencio (Eds.). Association for Computational Linguistics, 2245–2262
Ioana Baldini, Dennis Wei, Karthikeyan Natesan Ramamurthy, Moninder Singh, and Mikhail Yurochkin. 2022 · 2022
Earlier work this paper cites.
Distributionally Robust Finetuning BERT for Covariate Drift in Spoken Language Understanding. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2022, Dublin, Ireland, May 22-27, 2022 , Smaranda Muresan, Preslav Nakov, and Aline Villavicencio (Eds.). Association for Computational Linguistics, 1970–1985
Samuel Broscheit, Quynh Do, and Judith Gaspers. 2022 · 2022
Earlier work this paper cites.
What Does it Mean for a Language Model to Preserve Privacy?. In FAccT ’22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21 - 24, 2022 . ACM, 2280–2292
Hannah Brown, Katherine Lee, Fatemehsadat Mireshghallah, Reza Shokri, and Florian Tramèr. 2022 · 2022
Earlier work this paper cites.
ATTRITION: Attacking Static Hardware Trojan Detection Techniques Using Reinforcement Learning. In Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, CCS 2022, Los Angeles, CA, USA, November 7-11, 2022 , Heng Yin, Angelos Stavrou, Cas Cremers, and Elaine Shi (Eds.). ACM, 1275–1289
Vasudev Gohil, Hao Guo, Satwik Patnaik, and Jeyavijayan Rajendran. 2022 · 2022
Earlier work this paper cites.
An Empirical Study of Artifacts and Security Risks in the Pre-trained Model Supply Chain. In Proceedings of the 2022 ACM Workshop on Software Supply Chain Offensive Research and Ecosystem Defenses, SCORED2022, Los Angeles, CA, USA, 7 November 2022 , Santiago Torres-Arias, Marcela S. Melara, and Laurent Simon (Eds.). ACM, 105–114
Wenxin Jiang, Nicholas Synovic, Rohan Sethi, Aryan Indarapu, Matt Hyatt, Taylor R. Schorlemmer, George K. Thiruvathukal, and James C. Davis. 2022 · 2022
Earlier work this paper cites.
Factuality Enhanced Language Models for Open-Ended Text Generation. In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022 , Sanmi Koyejo, S. Mohamed, A. Agarwal, Danielle Belgrave, K. Cho, and A. Oh (Eds.)
Nayeon Lee, Wei Ping, Peng Xu, Mostofa Patwary, Pascale Fung, Mohammad Shoeybi, and Bryan Catanzaro. 2022 · 2022
Earlier work this paper cites.
TruthfulQA: Measuring How Models Mimic Human Falsehoods. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2022, Dublin, Ireland, May 22-27, 2022 , Smaranda Muresan, Preslav Nakov, and Aline Villavicencio (Eds.). Association for Computational Linguistics, 3214–3252
Stephanie Lin, Jacob Hilton, and Owain Evans. 2022 · 2022
Earlier work this paper cites.
Demystifying the Vulnerability Propagation and Its Evolution via Dependency Trees in the NPM Ecosystem. In 44th IEEE/ACM 44th International Conference on Software Engineering, ICSE 2022, Pittsburgh, PA, USA, May 25-27, 2022 . ACM, 672–684
Chengwei Liu, Sen Chen, Lingling Fan, Bihuan Chen, Yang Liu, and Xin Peng. 2022a · 2022
Earlier work this paper cites.
Data Contamination: From Memorization to Exploitation. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), ACL 2022, Dublin, Ireland, May 22-27, 2022 , Smaranda Muresan, Preslav Nakov, and Aline Villavicencio (Eds.). Association for Computational Linguistics, 157–165
Inbal Magar and Roy Schwartz. 2022 · 2022
Earlier work this paper cites.
Training language models to follow instructions with human feedback. In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022 , Sanmi Koyejo, S. Mohamed, A. Agarwal, Danielle Belgrave, K. Cho, and A. Oh (Eds.)
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul F. Christiano, Jan Leike, and Ryan Lowe. 2022 · 2022
Earlier work this paper cites.
The Text Anonymization Benchmark (TAB): A Dedicated Corpus and Evaluation Framework for Text Anonymization
Ildikó Pilán, Pierre Lison, Lilja Øvrelid, Anthi Papadopoulou, David Sánchez, and Montserrat Batet. 2022 · 2022
Earlier work this paper cites.
Maintainability Challenges in ML: A Systematic Literature Review. In 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022, Maspalomas, Gran Canaria, Spain, 31 August - 2 September 2022 , Gustavo Marrero Callicó, Regina Hebig, and Andreas Wortmann (Eds.). IEEE, 60–67
Karthik Shivashankar and Antonio Martini. 2022 · 2022
Earlier work this paper cites.
Upstream Mitigation Is Not All You Need: Testing the Bias Transfer Hypothesis in Pre-Trained Language Models. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2022, Dublin, Ireland, May 22-27, 2022 , Smaranda Muresan, Preslav Nakov, and Aline Villavicencio (Eds.). Association for Computational Linguistics, 3524–3542
Ryan Steed, Swetasudha Panda, Ari Kobren, and Michael L. Wick. 2022 · 2022
Earlier work this paper cites.
Never trust, always verify : a roadmap for Trustworthy AI?
Lionel Nganyewou Tidjon and Foutse Khomh. 2022 · 2022
Earlier work this paper cites.
Taxonomy of Risks posed by Language Models. In FAccT ’22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21 - 24, 2022 . ACM, 214–229
Laura Weidinger, Jonathan Uesato, Maribeth Rauh, Conor Griffin, Po-Sen Huang, John Mellor, Amelia Glaese, Myra Cheng, Borja Balle, Atoosa Kasirzadeh, Courtney Biles, Sasha Brown, Zac Kenton, Will Hawkins, Tom Stepleton, Abeba Birhane, Lisa Anne Hendricks, Laura Rimell, William Isaac, Julia Haas, Sean Legassick, Geoffrey Irving, and Iason Gabriel. 2022 · 2022
Earlier work this paper cites.
From Dense to Sparse: Contrastive Pruning for Better Pre-trained Language Model Compression. In Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI 2022, Thirty-Fourth Conference on Innovative Applications of Artificial Intelligence, IAAI 2022, The Twelveth Symposium on Educational Advances in Artificial Intelligence, EAAI 2022 Virtual Event, February 22 - March 1, 2022 . AAAI Press, 11547–11555
Runxin Xu, Fuli Luo, Chengyu Wang, Baobao Chang, Jun Huang, Songfang Huang, and Fei Huang. 2022 · 2022
Earlier work this paper cites.
Graphics Peeping Unit: Exploiting EM Side-Channel Information of GPUs to Eavesdrop on Your Neighbors. In 43rd IEEE Symposium on Security and Privacy, SP 2022, San Francisco, CA, USA, May 22-26, 2022 . IEEE, 1440–1457
Zihao Zhan, Zhenkai Zhang, Sisheng Liang, Fan Yao, and Xenofon D. Koutsoukos. 2022 · 2022
Earlier work this paper cites.
Not What You’ve Signed Up For: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection. In Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security, AISec 2023, Copenhagen, Denmark, 30 November 2023 , Maura Pintor, Xinyun Chen, and Florian Tramèr (Eds.). ACM, 79–90
Sahar Abdelnabi, Kai Greshake, Shailesh Mishra, Christoph Endres, Thorsten Holz, and Mario Fritz. 2023 · 2023
Earlier work this paper cites.
Gemini: A Family of Highly Capable Multimodal Models
Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M. Dai, Anja Hauth, Katie Millican, David Silver, Slav Petrov, Melvin Johnson, Ioannis Antonoglou, Julian Schrittwieser, Amelia Glaese, Jilin Chen, Emily Pitler, Timothy P. Lillicrap, Angeliki Lazaridou, Orhan Firat, James Molloy, Michael Isard, Paul Ronald Barham, Tom Hennigan, Benjamin Lee, Fabio Viola, Malcolm Reynolds, Yuanzhong Xu, Ryan Doherty, Eli Collins, Clemens Meyer, Eliza Rutherford, Erica Moreira, Kareem Ayoub, Megha Goel, George Tucker, Enrique Piqueras, Maxim Krikun, Iain Barr, Nikolay Savinov, Ivo Danihelka, Becca Roelofs, Anaïs White, Anders Andreassen, Tamara von Glehn, Lakshman Yagati, Mehran Kazemi, Lucas Gonzalez, Misha Khalman, Jakub Sygnowski, and et al. 2023 · 2023
Earlier work this paper cites.
Towards Building a Robust Toxicity Predictor. In Proceedings of the The 61st Annual Meeting of the Association for Computational Linguistics: Industry Track, ACL 2023, Toronto, Canada, July 9-14, 2023 , Sunayana Sitaram, Beata Beigman Klebanov, and Jason D. Williams (Eds.). Association for Computational Linguistics, 581–598
Dmitriy Bespalov, Sourav Bhabesh, Yi Xiang, Liutong Zhou, and Yanjun Qi. 2023 · 2023
Earlier work this paper cites.
Purple Llama CyberSecEval: A Secure Coding Benchmark for Language Models
Manish Bhatt, Sahana Chennabasappa, Cyrus Nikolaidis, Shengye Wan, Ivan Evtimov, Dominik Gabi, Daniel Song, Faizan Ahmad, Cornelius Aschermann, Lorenzo Fontana, Sasha Frolov, Ravi Prakash Giri, Dhaval Kapil, Yiannis Kozyrakis, David LeBlanc, James Milazzo, Aleksandar Straumann, Gabriel Synnaeve, Varun Vontimitta, Spencer Whitman, and Joshua Saxe. 2023 · 2023
Earlier work this paper cites.
Into the LAION’s Den: Investigating Hate in Multimodal Datasets. In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023 , Alice Oh, Tristan Naumann, Amir Globerson, Kate Saenko, Moritz Hardt, and Sergey Levine (Eds.)
Abeba Birhane, Vinay Uday Prabhu, Sanghyun Han, Vishnu Boddeti, and Sasha Luccioni. 2023 · 2023
Earlier work this paper cites.
Extracting Training Data from Diffusion Models. In 32nd USENIX Security Symposium, USENIX Security 2023, Anaheim, CA, USA, August 9-11, 2023 , Joseph A. Calandrino and Carmela Troncoso (Eds.). USENIX Association, 5253–5270
Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramèr, Borja Balle, Daphne Ippolito, and Eric Wallace. 2023 · 2023
Earlier work this paper cites.
FELM: Benchmarking Factuality Evaluation of Large Language Models. In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023 , Alice Oh, Tristan Naumann, Amir Globerson, Kate Saenko, Moritz Hardt, and Sergey Levine (Eds.)
Shiqi Chen, Yiran Zhao, Jinghan Zhang, I-Chun Chern, Siyang Gao, Pengfei Liu, and Junxian He. 2023 · 2023
Earlier work this paper cites.
Reusing Deep Learning Models: Challenges and Directions in Software Engineering. In IEEE John Vincent Atanasoff International Symposium on Modern Computing, JVA 2023, Chicago, IL, USA, July 5-6, 2023 , Shaukat Ali, Claudio A. Ardagna, Nimanthi L. Atukorala, Johanna Barzen, Carl K. Chang, Rong Chang, Jing Fan, Ismael Faro, Sebastian Feld, Geoffrey Fox, Zhi Jin, Frank Leymann, Florian Neukart, Salvador de la Puente, and Manuel Wimmer (Eds.). IEEE, 17–30
James C. Davis, Purvish Jajal, Wenxin Jiang, Taylor R. Schorlemmer, Nicholas Synovic, and George K. Thiruvathukal. 2023 · 2023
Earlier work this paper cites.
Benchmark Probing: Investigating Data Leakage in Large Language Models. In NeurIPS 2023 Workshop on Backdoors in Deep Learning - The Good, the Bad, and the Ugly
Chunyuan Deng, Yilun Zhao, Xiangru Tang, Mark Gerstein, and Arman Cohan. 2024b · 2023
Earlier work this paper cites.
CodeScore: Evaluating Code Generation by Learning Code Execution
Yihong Dong, Jiazheng Ding, Xue Jiang, Zhuo Li, Ge Li, and Zhi Jin. 2023 · 2023
Earlier work this paper cites.
LMentry: A Language Model Benchmark of Elementary Language Tasks. In Findings of the Association for Computational Linguistics: ACL 2023, Toronto, Canada, July 9-14, 2023 , Anna Rogers, Jordan L. Boyd-Graber, and Naoaki Okazaki (Eds.). Association for Computational Linguistics, 10476–10501
Avia Efrat, Or Honovich, and Omer Levy. 2023 · 2023
Earlier work this paper cites.
Should ChatGPT be biased? Challenges and risks of bias in large language models
Emilio Ferrara. 2023 · 2023
Earlier work this paper cites.
Misusing Tools in Large Language Models With Visual Adversarial Examples
Xiaohan Fu, Zihan Wang, Shuheng Li, Rajesh K. Gupta, Niloofar Mireshghallah, Taylor Berg-Kirkpatrick, and Earlence Fernandes. 2023 · 2023
Earlier work this paper cites.
Bias and Fairness in Large Language Models: A Survey
Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow, Md. Mehrab Tanjim, Sungchul Kim, Franck Dernoncourt, Tong Yu, Ruiyi Zhang, and Nesreen K. Ahmed. 2023 · 2023
Earlier work this paper cites.
RARR: Researching and Revising What Language Models Say, Using Language Models. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2023, Toronto, Canada, July 9-14, 2023 , Anna Rogers, Jordan L. Boyd-Graber, and Naoaki Okazaki (Eds.). Association for Computational Linguistics, 16477–16508
Luyu Gao, Zhuyun Dai, Panupong Pasupat, Anthony Chen, Arun Tejasvi Chaganty, Yicheng Fan, Vincent Y. Zhao, Ni Lao, Hongrae Lee, Da-Cheng Juan, and Kelvin Guu. 2023 · 2023
Earlier work this paper cites.
DETERRENT: Detecting Trojans Using Reinforcement Learning
Vasudev Gohil, Satwik Patnaik, Hao Guo, Dileep Kalathil, and Jeyavijayan Rajendran. 2024 · 2023
Earlier work this paper cites.
Data Contamination Quiz: A Tool to Detect and Estimate Contamination in Large Language Models
Shahriar Golchin and Mihai Surdeanu. 2023 · 2023
Earlier work this paper cites.
What can Large Language Models do in chemistry? A comprehensive benchmark on eight tasks. In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023 , Alice Oh, Tristan Naumann, Amir Globerson, Kate Saenko, Moritz Hardt, and Sergey Levine (Eds.)
Taicheng Guo, Kehan Guo, Bozhao Nan, Zhenwen Liang, Zhichun Guo, Nitesh V. Chawla, Olaf Wiest, and Xiangliang Zhang. 2023a · 2023
Earlier work this paper cites.
An Empirical Study of Malicious Code In PyPI Ecosystem. In 38th IEEE/ACM International Conference on Automated Software Engineering, ASE 2023, Luxembourg, September 11-15, 2023 . IEEE, 166–177
Wenbo Guo, Zhengzi Xu, Chengwei Liu, Cheng Huang, Yong Fang, and Yang Liu. 2023b · 2023
Earlier work this paper cites.
A Comprehensive Survey on Vector Database: Storage and Retrieval Technique, Challenge
Yikun Han, Chunjiang Liu, and Pengfei Wang. 2023 · 2023
Earlier work this paper cites.
Spear Phishing With Large Language Models
Julian Hazell. 2023 · 2023
Earlier work this paper cites.
Flames: Benchmarking Value Alignment of Chinese Large Language Models
Kexin Huang, Xiangyang Liu, Qianyu Guo, Tianxiang Sun, Jiawei Sun, Yaru Wang, Zeyang Zhou, Yixu Wang, Yan Teng, Xipeng Qiu, Yingchun Wang, and Dahua Lin. 2023 · 2023
Earlier work this paper cites.
BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset. In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023 , Alice Oh, Tristan Naumann, Amir Globerson, Kate Saenko, Moritz Hardt, and Sergey Levine (Eds.)
Jiaming Ji, Mickel Liu, Josef Dai, Xuehai Pan, Chi Zhang, Ce Bian, Boyuan Chen, Ruiyang Sun, Yizhou Wang, and Yaodong Yang. 2023b · 2023
Cited alongside, same era.
Survey on Open-source Software Supply Chain Security
Shouling Ji, Qinying Wang, Anying Chen, Binbin Zhao, Tong Ye, Xuhong Zhang, Jingzheng Wu, Yun Li, Jianwei Yin, and Yanjun Wu. 2023c · 2023
Cited alongside, same era.
Survey of Hallucination in Natural Language Generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Yejin Bang, Andrea Madotto, and Pascale Fung. 2023a · 2023
Cited alongside, same era.
Towards Mitigating Hallucination in Large Language Models via Self-Reflection
Ziwei Ji, Tiezheng Yu, Yan Xu, Nayeon Lee, Etsuko Ishii, and Pascale Fung. 2023d · 2023
Cited alongside, same era.
Hijacking Safetensors Conversion on Hugging Face
Eoin Wickens, Kasimir Schulz. 2024 · 2024
Closest in time.
Hugging Face
Hugging Face. 2024 · 2024
Closest in time.
The Foundation Model Transparency Index
Center for Research on Foundation Models (CRFM). 2024 · 2024
Closest in time.
Survey on Open Source Software Supply Chains
Kai Gao, Hao He, Bing Xie, and Minghui Zhou. 2024 · 2024
Closest in time.
MART: Improving LLM Safety with Multi-round Automatic Red-Teaming. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), NAACL 2024, Mexico City, Mexico, June 16-21, 2024 , Kevin Duh, Helena Gómez-Adorno, and Steven Bethard (Eds.). Association for Computational Linguistics, 1927–1937
Suyu Ge, Chunting Zhou, Rui Hou, Madian Khabsa, Yi-Chia Wang, Qifan Wang, Jiawei Han, and Yuning Mao. 2024 · 2024
Closest in time.
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alphaXiv is searching for related work…
An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry. In 45th IEEE/ACM International Conference on Software Engineering, ICSE 2023, Melbourne, Australia, May 14-20, 2023 . IEEE, 2463–2475
Wenxin Jiang, Nicholas Synovic, Matt Hyatt, Taylor R. Schorlemmer, Rohan Sethi, Yung-Hsiang Lu, George K. Thiruvathukal, and James C. Davis. 2023 · 2023
Cited alongside, same era.
Large Language Models Struggle to Learn Long-Tail Knowledge. In International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA (Proceedings of Machine Learning Research, Vol. 202) , Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, and Jonathan Scarlett (Eds.). PMLR, 15696–15707
Nikhil Kandpal, Haikang Deng, Adam Roberts, Eric Wallace, and Colin Raffel. 2023 · 2023
Cited alongside, same era.
Copyright Violations and Large Language Models. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, Singapore, December 6-10, 2023 , Houda Bouamor, Juan Pino, and Kalika Bali (Eds.). Association for Computational Linguistics, 7403–7412
Antonia Karamolegkou, Jiaang Li, Li Zhou, and Anders Søgaard. 2023 · 2023
Cited alongside, same era.
Assessing the Vulnerabilities of the Open-Source Artificial Intelligence (AI) Landscape: A Large-Scale Analysis of the Hugging Face Platform. In IEEE International Conference on Intelligence and Security Informatics, ISI 2023, Charlotte, NC, USA, October 2-3, 2023 . IEEE, 1–6
Adhishree Kathikar, Aishwarya Nair, Ben Lazarine, Agrim Sachdeva, and Sagar Samtani. 2023 · 2023
Cited alongside, same era.
Trustworthy Artificial Intelligence: A Review
Davinder Kaur, Suleyman Uslu, Kaley J. Rittichier, and Arjan Durresi. 2023 · 2023
Cited alongside, same era.
Generative AI meets Responsible AI: Practical Challenges and Opportunities. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023, Long Beach, CA, USA, August 6-10, 2023 , Ambuj K. Singh, Yizhou Sun, Leman Akoglu, Dimitrios Gunopulos, Xifeng Yan, Ravi Kumar, Fatma Ozcan, and Jieping Ye (Eds.). ACM, 5805–5806
Krishnaram Kenthapadi, Himabindu Lakkaraju, and Nazneen Rajani. 2023 · 2023
Cited alongside, same era.
ProPILE: Probing Privacy Leakage in Large Language Models. In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023 , Alice Oh, Tristan Naumann, Amir Globerson, Kate Saenko, Moritz Hardt, and Sergey Levine (Eds.)
Siwon Kim, Sangdoo Yun, Hwaran Lee, Martin Gubri, Sungroh Yoon, and Seong Joon Oh. 2023 · 2023
Cited alongside, same era.
Similarity of Neural Network Models: A Survey of Functional and Representational Measures
Max Klabunde, Tobias Schumacher, Markus Strohmaier, and Florian Lemmerich. 2023 · 2023
Cited alongside, same era.
Time Travel in LLMs: Tracing Data Contamination in Large Language Models. In The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024 . OpenReview.net
Shahriar Golchin and Mihai Surdeanu. 2024 · 2024
Closest in time.
Xiezhi: An Ever-Updating Benchmark for Holistic Domain Knowledge Evaluation. In Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence, IAAI 2024, Fourteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2014, February 20-27, 2024, Vancouver, Canada , Michael J. Wooldridge, Jennifer G. Dy, and Sriraam Natarajan (Eds.). AAAI Press, 18099–18107
Zhouhong Gu, Xiaoxuan Zhu, Haoning Ye, Lin Zhang, Jianchen Wang, Yixin Zhu, Sihang Jiang, Zhuozhi Xiong, Zihan Li, Weijie Wu, Qianyu He, Rui Xu, Wenhao Huang, Jingping Liu, Zili Wang, Shusen Wang, Weiguo Zheng, Hongwei Feng, and Yanghua Xiao. 2024 · 2024
Closest in time.
Detecting and Preventing Hallucinations in Large Vision Language Models. In Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence, IAAI 2024, Fourteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2014, February 20-27, 2024, Vancouver, Canada , Michael J. Wooldridge, Jennifer G. Dy, and Sriraam Natarajan (Eds.). AAAI Press, 18135–18143
Anisha Gunjal, Jihan Yin, and Erhan Bas. 2024 · 2024
Closest in time.
Large Language Model Based Multi-agents: A Survey of Progress and Challenges. In Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI 2024, Jeju, South Korea, August 3-9, 2024 . ijcai.org, 8048–8057
Taicheng Guo, Xiuying Chen, Yaqi Wang, Ruidi Chang, Shichao Pei, Nitesh V. Chawla, Olaf Wiest, and Xiangliang Zhang. 2024 · 2024
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Hasan Abed Al Kader Hammoud, Umberto Michieli, Fabio Pizzati, Philip Torr, Adel Bibi, Bernard Ghanem, and Mete Ozay. 2024 · 2024
Closest in time.
The Emerged Security and Privacy of LLM Agent: A Survey with Case Studies
Feng He, Tianqing Zhu, Dayong Ye, Bo Liu, Wanlei Zhou, and Philip S. Yu. 2024c · 2024
Closest in time.
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Jinwen He, Yujia Gong, Zijin Lin, Cheng’an Wei, Yue Zhao, and Kai Chen. 2024a · 2024
Closest in time.
Yifeng He, Ethan Wang, Yuyang Rong, Zifei Cheng, and Hao Chen. 2024b · 2024
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On the (In)Security of LLM App Stores
Xinyi Hou, Yanjie Zhao, and Haoyu Wang. 2024a · 2024
Closest in time.
Voices from the Frontier: A Comprehensive Analysis of the OpenAI Developer Forum
Xinyi Hou, Yanjie Zhao, and Haoyu Wang. 2024b · 2024
Closest in time.
Empirical Analysis of Vulnerabilities Life Cycle in Golang Ecosystem. In Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, ICSE 2024, Lisbon, Portugal, April 14-20, 2024 . ACM, 212:1–212:13
Jinchang Hu, Lyuye Zhang, Chengwei Liu, Sen Yang, Song Huang, and Yang Liu. 2024 · 2024
Closest in time.
datasets
HuggingFace. 2024 · 2024
Closest in time.
Cybercriminal sells tool to hide malware in AMD, NVIDIA GPUs
Ionut Ilascu. 2021 · 2024
Closest in time.
CVE-2023-1177 (MLFlow Path Traversal)
iumiro. 2023 · 2024
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LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code
Naman Jain, King Han, Alex Gu, Wen-Ding Li, Fanjia Yan, Tianjun Zhang, Sida Wang, Armando Solar-Lezama, Koushik Sen, and Ion Stoica. 2024a · 2024
Closest in time.
LLM-Assisted Code Cleaning For Training Accurate Code Generators. In The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024 . OpenReview.net
Naman Jain, Tianjun Zhang, Wei-Lin Chiang, Joseph E. Gonzalez, Koushik Sen, and Ion Stoica. 2024b · 2024
Closest in time.
On the Risks of Overreliance on a Single AI Cloud Services Provider
Jair Ribeiro. 2024 · 2024
Closest in time.
From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future
Haolin Jin, Linghan Huang, Haipeng Cai, Jun Yan, Bo Li, and Huaming Chen. 2024 · 2024
Closest in time.
An Exploratory Investigation into Code License Infringements in Large Language Model Training Datasets. In Proceedings of the 2024 IEEE/ACM First International Conference on AI Foundation Models and Software Engineering, FORGE 2024, Lisbon, Portugal, 14 April 2024 , David Lo, Xin Xia, Massimiliano Di Penta, and Xing Hu (Eds.). ACM, 74–85
Jonathan Katzy, Razvan Mihai Popescu, Arie van Deursen, and Maliheh Izadi. 2024a · 2024
Closest in time.
An Exploratory Investigation into Code License Infringements in Large Language Model Training Datasets. In Proceedings of the 2024 IEEE/ACM First International Conference on AI Foundation Models and Software Engineering, FORGE 2024, Lisbon, Portugal, 14 April 2024 , David Lo, Xin Xia, Massimiliano Di Penta, and Xing Hu (Eds.). ACM, 74–85
Jonathan Katzy, Razvan Mihai Popescu, Arie van Deursen, and Maliheh Izadi. 2024b · 2024
Closest in time.
Harnessing the Power of General-Purpose LLMs in Hardware Trojan Design. In Applied Cryptography and Network Security Workshops - ACNS 2024 Satellite Workshops, AIBlock, AIHWS, AIoTS, SCI, AAC, SiMLA, LLE, and CIMSS, Abu Dhabi, United Arab Emirates, March 5-8, 2024, Proceedings, Part I (Lecture Notes in Computer Science, Vol. 14586) , Martin Andreoni (Ed.). Springer, 176–194
Georgios Kokolakis, Athanasios Moschos, and Angelos D. Keromytis. 2024 · 2024
Closest in time.
LangChain
LangChain-AI. 2024 · 2024
Closest in time.
Task Contamination: Language Models May Not Be Few-Shot Anymore. In Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence, IAAI 2024, Fourteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2014, February 20-27, 2024, Vancouver, Canada , Michael J. Wooldridge, Jennifer G. Dy, and Sriraam Natarajan (Eds.). AAAI Press, 18471–18480
Changmao Li and Jeffrey Flanigan. 2024 · 2024
Closest in time.
Digger: Detecting Copyright Content Mis-usage in Large Language Model Training
Haodong Li, Gelei Deng, Yi Liu, Kailong Wang, Yuekang Li, Tianwei Zhang, Yang Liu, Guoai Xu, Guosheng Xu, and Haoyu Wang. 2024a · 2024
Closest in time.
Measuring and Controlling Persona Drift in Language Model Dialogs
Kenneth Li, Tianle Liu, Naomi Bashkansky, David Bau, Fernanda B. Viégas, Hanspeter Pfister, and Martin Wattenberg. 2024c · 2024
Closest in time.
LatestEval: Addressing Data Contamination in Language Model Evaluation through Dynamic and Time-Sensitive Test Construction. In Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence, IAAI 2024, Fourteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2014, February 20-27, 2024, Vancouver, Canada , Michael J. Wooldridge, Jennifer G. Dy, and Sriraam Natarajan (Eds.). AAAI Press, 18600–18607
Yucheng Li, Frank Guerin, and Chenghua Lin. 2024b · 2024
Closest in time.
Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security
Yuanchun Li, Hao Wen, Weijun Wang, Xiangyu Li, Yizhen Yuan, Guohong Liu, Jiacheng Liu, Wenxing Xu, Xiang Wang, Yi Sun, Rui Kong, Yile Wang, Hanfei Geng, Jian Luan, Xuefeng Jin, Zilong Ye, Guanjing Xiong, Fan Zhang, Xiang Li, Mengwei Xu, Zhijun Li, Peng Li, Yang Liu, Ya-Qin Zhang, and Yunxin Liu. 2024e · 2024
Closest in time.
What’s documented in AI? Systematic Analysis of 32K AI Model Cards
Weixin Liang, Nazneen Rajani, Xinyu Yang, Ezinwanne Ozoani, Eric Wu, Yiqun Chen, Daniel Scott Smith, and James Zou. 2024 · 2024
Closest in time.
Chain of Hindsight aligns Language Models with Feedback. In The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024 . OpenReview.net
Hao Liu, Carmelo Sferrazza, and Pieter Abbeel. 2024b · 2024
Closest in time.
Large Language Model-Based Agents for Software Engineering: A Survey
Junwei Liu, Kaixin Wang, Yixuan Chen, Xin Peng, Zhenpeng Chen, Lingming Zhang, and Yiling Lou. 2024c · 2024
Closest in time.
RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems. In The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024 . OpenReview.net
Tianyang Liu, Canwen Xu, and Julian J. McAuley. 2024d · 2024
Closest in time.
Datasets for Large Language Models: A Comprehensive Survey
Yang Liu, Jiahuan Cao, Chongyu Liu, Kai Ding, and Lianwen Jin. 2024a · 2024
Closest in time.
Trained Without My Consent: Detecting Code Inclusion In Language Models Trained on Code
Vahid Majdinasab, Amin Nikanjam, and Foutse Khomh. 2024 · 2024
Closest in time.
HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal. In Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024 . OpenReview.net
Mantas Mazeika, Long Phan, Xuwang Yin, Andy Zou, Zifan Wang, Norman Mu, Elham Sakhaee, Nathaniel Li, Steven Basart, Bo Li, David A. Forsyth, and Dan Hendrycks. 2024 · 2024
Closest in time.
Inadequacies of Large Language Model Benchmarks in the Era of Generative Artificial Intelligence
Timothy R. McIntosh, Teo Susnjak, Tong Liu, Paul A. Watters, and Malka N. Halgamuge. 2024 · 2024
Closest in time.
Copyright Traps for Large Language Models. In Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024 . OpenReview.net
Matthieu Meeus, Igor Shilov, Manuel Faysse, and Yves-Alexandre de Montjoye. 2024 · 2024
Closest in time.
Kai Mei, Zelong Li, Shuyuan Xu, Ruosong Ye, Yingqiang Ge, and Yongfeng Zhang. 2024 · 2024
Closest in time.
Generating Benchmarks for Factuality Evaluation of Language Models. In Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2024 - Volume 1: Long Papers, St. Julian’s, Malta, March 17-22, 2024 , Yvette Graham and Matthew Purver (Eds.). Association for Computational Linguistics, 49–66
Dor Muhlgay, Ori Ram, Inbal Magar, Yoav Levine, Nir Ratner, Yonatan Belinkov, Omri Abend, Kevin Leyton-Brown, Amnon Shashua, and Yoav Shoham. 2024 · 2024
Closest in time.
Legit Discovers "AI Jacking" Vulnerability in Popular Hugging Face AI Platform
Nadav Noy. 2023 · 2024
Closest in time.
SocialStigmaQA: A Benchmark to Uncover Stigma Amplification in Generative Language Models. In Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence, IAAI 2024, Fourteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2014, February 20-27, 2024, Vancouver, Canada , Michael J. Wooldridge, Jennifer G. Dy, and Sriraam Natarajan (Eds.). AAAI Press, 21454–21462
Manish Nagireddy, Lamogha Chiazor, Moninder Singh, and Ioana Baldini. 2024 · 2024
Closest in time.
Hundreds of LLM Servers Expose Corporate, Health & Other Online Data
Nate Nelson. 2024 · 2024
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New Hugging Face Vulnerability Exposes AI Models to Supply Chain Attacks
The Hacker News. 2024 · 2024
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Security Bulletin: NVIDIA DGX A100 - January 2024
NVIDIA. 2024 · 2024
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Introducing the GPT Store
OpenAI. 2024 · 2024
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OmniQuant
OpenGVLab. 2024 · 2024
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Proving Test Set Contamination in Black-Box Language Models. In The Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11, 2024 . OpenReview.net
Yonatan Oren, Nicole Meister, Niladri S. Chatterji, Faisal Ladhak, and Tatsunori Hashimoto. 2024 · 2024
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OWASP Top 10 for Large Language Model Applications
OWASP. 2024a · 2024
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OWASP Top 10 LLM V2 Candidates
OWASP. 2024b · 2024
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Supply-Chain Attacks in LLMs: From GGUF model format metadata RCE, to State-of-The-Art NLP Project RCEs
Patrick Peng. 2024 · 2024
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How do Hugging Face Models Document Datasets, Bias, and Licenses? An Empirical Study. In Proceedings of the 32nd IEEE/ACM International Conference on Program Comprehension, ICPC 2024, Lisbon, Portugal, April 15-16, 2024 , Igor Steinmacher, Mario Linares-Vásquez, Kevin Patrick Moran, and Olga Baysal (Eds.). ACM, 370–381
Federica Pepe, Vittoria Nardone, Antonio Mastropaolo, Gabriele Bavota, Gerardo Canfora, and Massimiliano Di Penta. 2024 · 2024
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Unveiling the Veil: A Comprehensive Analysis of Data Contamination in Leading Language Models
Mahesh Datta Sai Ponnuru, Likhitha Amasala, and Guna Garikipati. 2024 · 2024
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Visual Adversarial Examples Jailbreak Aligned Large Language Models. In Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence, IAAI 2024, Fourteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2014, February 20-27, 2024, Vancouver, Canada , Michael J. Wooldridge, Jennifer G. Dy, and Sriraam Natarajan (Eds.). AAAI Press, 21527–21536
Xiangyu Qi, Kaixuan Huang, Ashwinee Panda, Peter Henderson, Mengdi Wang, and Prateek Mittal. 2024 · 2024
Closest in time.
Ray: Productionizing and scaling Python ML workloads simply
Ray. 2024 · 2024
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Thousands of companies using Ray framework exposed to cyberattacks, researchers say
The Record. 2024 · 2024
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Practical LLM Security: Takeaways From a Year in the Trenches
Richard Harang. 2024 · 2024
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From MLOps to MLOops - Exposing the Attack Surface of Machine Learning Platforms
Shachar Menashe. 2024 · 2024
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Navigating the Cloud: Reflecting on the World’s 10 Biggest Outages and Critical Preventive Measures
Shaerul Haque J. 2024 · 2024
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CORECODE: A Common Sense Annotated Dialogue Dataset with Benchmark Tasks for Chinese Large Language Models. In Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence, IAAI 2024, Fourteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2014, February 20-27, 2024, Vancouver, Canada , Michael J. Wooldridge, Jennifer G. Dy, and Sriraam Natarajan (Eds.). AAAI Press, 18952–18960
Dan Shi, Chaobin You, Jiantao Huang, Taihao Li, and Deyi Xiong. 2024c · 2024
Closest in time.
Efficient and Green Large Language Models for Software Engineering: Vision and the Road Ahead
Jieke Shi, Zhou Yang, and David Lo. 2024b · 2024
Closest in time.
WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback
Taiwei Shi, Zhuoer Wang, Longqi Yang, Ying-Chun Lin, Zexue He, Mengting Wan, Pei Zhou, Sujay Kumar Jauhar, Xiaofeng Xu, Xia Song, and Jennifer Neville. 2024a · 2024
Closest in time.
Rethinking Interpretability in the Era of Large Language Models
Chandan Singh, Jeevana Priya Inala, Michel Galley, Rich Caruana, and Jianfeng Gao. 2024 · 2024
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RCE in Python NLTK (CVE-2024-39705)
Smartkeyss. 2024 · 2024
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LeftoverLocals: Listening to LLM Responses Through Leaked GPU Local Memory
Tyler Sorensen and Heidy Khlaaf. 2024 · 2024
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Is Llama 3.1 Really Open Source?
Sriram Parthasarathy. 2024 · 2024
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BOMs Away! Inside the Minds of Stakeholders: A Comprehensive Study of Bills of Materials for Software Systems. In Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, ICSE 2024, Lisbon, Portugal, April 14-20, 2024 . ACM, 44:1–44:13
Trevor Stalnaker, Nathan Wintersgill, Oscar Chaparro, Massimiliano Di Penta, Daniel M. Germán, and Denys Poshyvanyk. 2024 · 2024
Closest in time.
Dongxun Su, Yanjie Zhao, Xinyi Hou, Shenao Wang, and Haoyu Wang. 2024 · 2024
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LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions
Chuanneng Sun, Songjun Huang, and Dario Pompili. 2024b · 2024
Closest in time.
SciEval: A Multi-Level Large Language Model Evaluation Benchmark for Scientific Research. In Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence, IAAI 2024, Fourteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2014, February 20-27, 2024, Vancouver, Canada , Michael J. Wooldridge, Jennifer G. Dy, and Sriraam Natarajan (Eds.). AAAI Press, 19053–19061
Liangtai Sun, Yang Han, Zihan Zhao, Da Ma, Zhennan Shen, Baocai Chen, Lu Chen, and Kai Yu. 2024a · 2024
Closest in time.
Sparsity-Guided Holistic Explanation for LLMs with Interpretable Inference-Time Intervention. In Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence, IAAI 2024, Fourteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2014, February 20-27, 2024, Vancouver, Canada , Michael J. Wooldridge, Jennifer G. Dy, and Sriraam Natarajan (Eds.). AAAI Press, 21619–21627
Zhen Tan, Tianlong Chen, Zhenyu Zhang, and Huan Liu. 2024 · 2024
Closest in time.
Deep Learning Model Reuse in the HuggingFace Community: Challenges, Benefit and Trends. In IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2024, Rovaniemi, Finland, March 12-15, 2024 . IEEE, 512–523
Mina Taraghi, Gianolli Dorcelus, Armstrong Foundjem, Florian Tambon, and Foutse Khomh. 2024 · 2024
Closest in time.
TensorFlow
TensorFlow. 2024 · 2024
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Models are code: A deep dive into security risks in TensorFlow and Keras
Tom Bonner. 2023 · 2024
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A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models
S. M. Towhidul Islam Tonmoy, S. M. Mehedi Zaman, Vinija Jain, Anku Rani, Vipula Rawte, Aman Chadha, and Amitava Das. 2024 · 2024
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Generative AI Exposure to PyTorch’s Distributed RPC and CVE-2024–5480 Vulnerability
Valdez Ladd. 2024 · 2024
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Exploring Multi-Lingual Bias of Large Code Models in Code Generation
Chaozheng Wang, Zongjie Li, Cuiyun Gao, Wenxuan Wang, Ting Peng, Hailiang Huang, Yuetang Deng, Shuai Wang, and Michael R. Lyu. 2024b · 2024
Closest in time.
ReposVul: A Repository-Level High-Quality Vulnerability Dataset. In Proceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings, ICSE Companion 2024, Lisbon, Portugal, April 14-20, 2024 . ACM, 472–483
Xinchen Wang, Ruida Hu, Cuiyun Gao, Xin-Cheng Wen, Yujia Chen, and Qing Liao. 2024a · 2024
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Large Model Agents: State-of-the-Art, Cooperation Paradigms, Security and Privacy, and Future Trends
Yuntao Wang, Yanghe Pan, Quan Zhao, Yi Deng, Zhou Su, Linkang Du, and Tom H. Luan. 2024c · 2024
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Agents in Software Engineering: Survey, Landscape, and Vision
Yanlin Wang, Wanjun Zhong, Yanxian Huang, Ensheng Shi, Min Yang, Jiachi Chen, Hui Li, Yuchi Ma, Qianxiang Wang, and Zibin Zheng. 2024d · 2024
Closest in time.
Weights & Biases: The AI Developer Platform
Weights & Biases. 2024 · 2024
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Fundamental Limitations of Alignment in Large Language Models. In Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024 . OpenReview.net
Yotam Wolf, Noam Wies, Oshri Avnery, Yoav Levine, and Amnon Shashua. 2024 · 2024
Closest in time.
A New Era in LLM Security: Exploring Security Concerns in Real-World LLM-based Systems
Fangzhou Wu, Ning Zhang, Somesh Jha, Patrick D. McDaniel, and Chaowei Xiao. 2024b · 2024
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The Dark Side of Function Calling: Pathways to Jailbreaking Large Language Models
Zihui Wu, Haichang Gao, Jianping He, and Ping Wang. 2024a · 2024
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RedAgent: Red Teaming Large Language Models with Context-aware Autonomous Language Agent
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Unveiling Memorization in Code Models. In Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, ICSE 2024, Lisbon, Portugal, April 14-20, 2024 . ACM, 72:1–72:13
Zhou Yang, Zhipeng Zhao, Chenyu Wang, Jieke Shi, Dongsun Kim, DongGyun Han, and David Lo. 2024 · 2024
Closest in time.
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Sibo Yi, Yule Liu, Zhen Sun, Tianshuo Cong, Xinlei He, Jiaxing Song, Ke Xu, and Qi Li. 2024 · 2024
Closest in time.
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Hao Yu, Bo Shen, Dezhi Ran, Jiaxin Zhang, Qi Zhang, Yuchi Ma, Guangtai Liang, Ying Li, Qianxiang Wang, and Tao Xie. 2024 · 2024
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AutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks
Yifan Zeng, Yiran Wu, Xiao Zhang, Huazheng Wang, and Qingyun Wu. 2024 · 2024
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Breaking Agents: Compromising Autonomous LLM Agents Through Malfunction Amplification
Boyang Zhang, Yicong Tan, Yun Shen, Ahmed Salem, Michael Backes, Savvas Zannettou, and Yang Zhang. 2024b · 2024
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Efficient Toxic Content Detection by Bootstrapping and Distilling Large Language Models. In Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence, IAAI 2024, Fourteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2014, February 20-27, 2024, Vancouver, Canada , Michael J. Wooldridge, Jennifer G. Dy, and Sriraam Natarajan (Eds.). AAAI Press, 21779–21787
Jiang Zhang, Qiong Wu, Yiming Xu, Cheng Cao, Zheng Du, and Konstantinos Psounis. 2024c · 2024
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GlitchProber: Advancing Effective Detection and Mitigation of Glitch Tokens in Large Language Models
Zhibo Zhang, Wuxia Bai, Yuxi Li, Mark Huasong Meng, Kailong Wang, Ling Shi, Li Li, Jun Wang, and Haoyu Wang. 2024a · 2024
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Models Are Codes: Towards Measuring Malicious Code Poisoning Attacks on Pre-trained Model Hubs
Jian Zhao, Shenao Wang, Yanjie Zhao, Xinyi Hou, Kailong Wang, Peiming Gao, Yuanchao Zhang, Chen Wei, and Haoyu Wang. 2024b · 2024
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Yanjie Zhao, Xinyi Hou, Shenao Wang, and Haoyu Wang. 2024a · 2024
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EasyJailbreak: A Unified Framework for Jailbreaking Large Language Models
Weikang Zhou, Xiao Wang, Limao Xiong, Han Xia, Yingshuang Gu, Mingxu Chai, Fukang Zhu, Caishuang Huang, Shihan Dou, Zhiheng Xi, Rui Zheng, Songyang Gao, Yicheng Zou, Hang Yan, Yifan Le, Ruohui Wang, Lijun Li, Jing Shao, Tao Gui, Qi Zhang, and Xuanjing Huang. 2024 · 2024
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Glitch Tokens in Large Language Models: Categorization Taxonomy and Effective Detection
Yuxi Li, Yi Liu, Gelei Deng, Ying Zhang, Wenjia Song, Ling Shi, Kailong Wang, Yuekang Li, Yang Liu, and Haoyu Wang. 2024d · 2097
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