Fetching the paper…
Reading the bibliography…
Refusal discovery is the task of identifying the full set of topics that a language model refuses to discuss.
Assessing post deletion in sina weibo: Multi-modal classification of hot topics, 2019
Meisam Navaki Arefi, Rajkumar Pandi, Michael Carl Tschantz, Jedidiah R. Crandall, King wa Fu, Dahlia Qiu Shi, and Miao Sha · 1906
Earlier work this paper cites.
How censorship in china allows government criticism but silences collective expression
Gary King, Jennifer Pan, and Margaret E Roberts · 2013
Earlier work this paper cites.
Reverse-engineering censorship in china: Randomized experimentation and participant observation
Gary King, Jennifer Pan, and Margaret E. Roberts · 2014
Earlier work this paper cites.
Every rose has its thorn: Censorship and surveillance on social video platforms in china
Jeffrey Knockel, Masashi Crete-Nishihata, Jason Q. Ng, Adam Senft, and Jedidiah R. Crandall · 2015
Earlier work this paper cites.
Weiboscope Open Data
King Wa Fu · 2017
Earlier work this paper cites.
Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
Earlier work this paper cites.
Gender shades: Intersectional accuracy disparities in commercial gender classification
Joy Buolamwini and Timnit Gebru · 2018
Earlier work this paper cites.
Auditing the personalization and composition of politically-related search engine results pages
Ronald E Robertson, David Lazer, and Christo Wilson · 2018
Earlier work this paper cites.
Explainable ai: A review of machine learning interpretability methods
Pantelis Linardatos, Vasilis Papastefanopoulos, and Sotiris Kotsiantis · 2020
Earlier work this paper cites.
The algorithmic audit: Working with vendors to validate radiology-ai algorithms—how we do it
Vidur Mahajan, Vasantha Kumar Venugopal, Murali Murugavel, and Harsh Mahajan · 2020
Earlier work this paper cites.
Linguistic fingerprints of internet censorship: The case of sina weibo
Kei Yin Ng, Anna Feldman, and Jing Peng · 2020
Earlier work this paper cites.
Mitigating bias in algorithmic hiring: evaluating claims and practices
Manish Raghavan, Solon Barocas, Jon Kleinberg, and Karen Levy · 2020
Earlier work this paper cites.
Saving face: Investigating the ethical concerns of facial recognition auditing
Inioluwa Deborah Raji, Timnit Gebru, Margaret Mitchell, Joy Buolamwini, Joonseok Lee, and Emily Denton · 2020
Earlier work this paper cites.
Multimodal datasets: misogyny, pornography, and malignant stereotypes
Abeba Birhane, Vinay Uday Prabhu, and Emmanuel Kahembwe · 2021
Earlier work this paper cites.
Extracting training data from large language models
Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, et al · 2021
Earlier work this paper cites.
Highly accurate protein structure prediction with alphafold
John M. Jumper, Richard Evans, Alexander Pritzel, Tim Green, Michael Figurnov, Olaf Ronneberger, Kathryn Tunyasuvunakool, Russ Bates, Augustin Žídek, Anna Potapenko, Alex Bridgland, Clemens Meyer, Simon A A Kohl, Andy Ballard, Andrew Cowie, Bernardino Romera-Paredes, Stanislav Nikolov, Rishub Jain, Jonas Adler, Trevor Back, Stig Petersen, David Reiman, Ellen Clancy, Michal Zielinski, Martin Steinegger, Michalina Pacholska, Tamas Berghammer, Sebastian Bodenstein, David Silver, Oriol Vinyals, Andrew W. Senior, Koray Kavukcuoglu, Pushmeet Kohli, and Demis Hassabis · 2021
Earlier work this paper cites.
Systematizing audit in algorithmic recruitment
Emre Kazim, Adriano Soares Koshiyama, Airlie Hilliard, and Roseline Polle · 2021
Earlier work this paper cites.
What’s in the box? a preliminary analysis of undesirable content in the common crawl corpus
Alexandra Sasha Luccioni and Joseph D Viviano · 2021
Earlier work this paper cites.
Finetuned language models are zero-shot learners
Jason Wei, Maarten Bosma, Vincent Y Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M Dai, and Quoc V Le · 2021
Earlier work this paper cites.
Openxai: Towards a transparent evaluation of model explanations
Chirag Agarwal, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, and Himabindu Lakkaraju · 2022
Earlier work this paper cites.
The medical algorithmic audit
Xiaoxuan Liu, Ben Glocker, Melissa M McCradden, Marzyeh Ghassemi, Alastair K Denniston, and Lauren Oakden-Rayner · 2022
Earlier work this paper cites.
Red-teaming the stable diffusion safety filter
Javier Rando, Daniel Paleka, David Lindner, Lennart Heim, and Florian Tramèr · 2022
Earlier work this paper cites.
Tackling climate change with machine learning
David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, et al · 2022
Earlier work this paper cites.
Ai capabilities can be significantly improved without expensive retraining
Alan Chan, Jean-Stanislas Denain, Pablo Villalobos, and Guillem Bas · 2023
Cited alongside, same era.
PV Charan, Hrushikesh Chunduri, P Mohan Anand, and Sandeep K Shukla · 2023
Cited alongside, same era.
Bias and debias in recommender system: A survey and future directions
Jiawei Chen, Hande Dong, Xiang Wang, Fuli Feng, Meng Wang, and Xiangnan He · 2023
Cited alongside, same era.
Nexus: A Brief History of Information Networks from the Stone Age to AI
Yuval Noah Harari · 2023
Cited alongside, same era.
Foundation models and fair use
Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A Lemley, and Percy Liang · 2023
Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Alex Vaughan, et al · 2024
Later among the works it cites.
Wildguard: Open one-stop moderation tools for safety risks, jailbreaks, and refusals of llms, 2024
Seungju Han, Kavel Rao, Allyson Ettinger, Liwei Jiang, Bill Yuchen Lin, Nathan Lambert, Yejin Choi, and Nouha Dziri · 2024
Later among the works it cites.
Sleeper agents: Training deceptive llms that persist through safety training
Evan Hubinger, Carson Denison, Jesse Mu, Mike Lambert, Meg Tong, Monte MacDiarmid, Tamera Lanham, Daniel M Ziegler, Tim Maxwell, Newton Cheng, et al · 2024
Later among the works it cites.
Wildteaming at scale: From in-the-wild jailbreaks to (adversarially) safer language models
Liwei Jiang, Kavel Rao, Seungju Han, Allyson Ettinger, Faeze Brahman, Sachin Kumar, Niloofar Mireshghallah, Ximing Lu, Maarten Sap, Yejin Choi, and Nouha Dziri · 2024
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
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, Ye Jin Bang, Andrea Madotto, and Pascale Fung · 2023
Cited alongside, same era.
Copyright violations and large language models
Antonia Karamolegkou, Jiaang Li, Li Zhou, and Anders Søgaard · 2023
Cited alongside, same era.
Evaluating language-model agents on realistic autonomous tasks
Megan Kinniment, Lucas Jun Koba Sato, Haoxing Du, Brian Goodrich, Max Hasin, Lawrence Chan, Luke Harold Miles, Tao R Lin, Hjalmar Wijk, Joel Burget, et al · 2023
Cited alongside, same era.
Large language models are zero-shot reasoners, 2023
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 2023
Cited alongside, same era.
Jailbreaking chatgpt via prompt engineering: An empirical study
Yi Liu, Gelei Deng, Zhengzi Xu, Yuekang Li, Yaowen Zheng, Ying Zhang, Lida Zhao, Tianwei Zhang, and Yang Liu · 2023
Cited alongside, same era.
Do the rewards justify the means? measuring trade-offs between rewards and ethical behavior in the machiavelli benchmark
Alexander Pan, Jun Shern Chan, Andy Zou, Nathaniel Li, Steven Basart, Thomas Woodside, Jonathan Ng, Hanlin Zhang, Scott Emmons, and Dan Hendrycks · 2023
Cited alongside, same era.
Ai deception: A survey of examples, risks, and potential solutions
Peter S Park, Simon Goldstein, Aidan O’Gara, Michael Chen, and Dan Hendrycks · 2023
Cited alongside, same era.
How successful are ai-discovered drugs in clinical trials? a first analysis and emerging lessons
Madura KP Jayatunga, Margaret Ayers, Lotte Bruens, Dhruv Jayanth, and Christoph Meier · 2024
Later among the works it cites.
T \ \backslash ” ulu 3: Pushing frontiers in open language model post-training
Nathan Lambert, Jacob Morrison, Valentina Pyatkin, Shengyi Huang, Hamish Ivison, Faeze Brahman, Lester James V Miranda, Alisa Liu, Nouha Dziri, Shane Lyu, et al · 2024
Later among the works it cites.
Harmbench: A standardized evaluation framework for automated red teaming and robust refusal
Mantas Mazeika, Long Phan, Xuwang Yin, Andy Zou, Zifan Wang, Norman Mu, Elham Sakhaee, Nathaniel Li, Steven Basart, Bo Li, David Forsyth, and Dan Hendrycks · 2024
Later among the works it cites.
Safety alignment should be made more than just a few tokens deep, 2024
Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, Xiao Ma, Subhrajit Roy, Ahmad Beirami, Prateek Mittal, and Peter Henderson · 2024
Later among the works it cites.
Can a.i. be blamed for a teen’s suicide?
Kevin Roose · 2024
Later among the works it cites.
Bypassing the safety training of open-source llms with priming attacks, 2024
Jason Vega, Isha Chaudhary, Changming Xu, and Gagandeep Singh · 2024
Later among the works it cites.
Backtracking improves generation safety, 2024
Yiming Zhang, Jianfeng Chi, Hailey Nguyen, Kartikeya Upasani, Daniel M. Bikel, Jason Weston, and Eric Michael Smith · 2024
Later among the works it cites.
When big data enables behavioral manipulation
Daron Acemoglu, Ali Makhdoumi, Azarakhsh Malekian, and Asuman Ozdaglar · 2025
Closest in time.
Large language models reflect the ideology of their creators, 2025
Maarten Buyl, Alexander Rogiers, Sander Noels, Guillaume Bied, Iris Dominguez-Catena, Edith Heiter, Iman Johary, Alexandru-Cristian Mara, Raphaël Romero, Jefrey Lijffijt, and Tijl De Bie · 2025
Closest in time.
Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning, 2025
DeepSeek-AI, Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, Xiaokang Zhang, Xingkai Yu, Yu Wu, Z. F. Wu, Zhibin Gou, Zhihong Shao, Zhuoshu Li, Ziyi Gao, Aixin Liu, Bing Xue, Bingxuan Wang, Bochao Wu, Bei Feng, Chengda Lu, Chenggang Zhao, Chengqi Deng, Chenyu Zhang, Chong Ruan, Damai Dai, Deli Chen, Dongjie Ji, Erhang Li, Fangyun Lin, Fucong Dai, Fuli Luo, Guangbo Hao, Guanting Chen, Guowei Li, H. Zhang, Han Bao, Hanwei Xu, Haocheng Wang, Honghui Ding, Huajian Xin, Huazuo Gao, Hui Qu, Hui Li, Jianzhong Guo, Jiashi Li, Jiawei Wang, Jingchang Chen, Jingyang Yuan, Junjie Qiu, Junlong Li, J. L. Cai, Jiaqi Ni, Jian Liang, Jin Chen, Kai Dong, Kai Hu, Kaige Gao, Kang Guan, Kexin Huang, Kuai Yu, Lean Wang, Lecong Zhang, Liang Zhao, Litong Wang, Liyue Zhang, Lei Xu, Leyi Xia, Mingchuan Zhang, Minghua Zhang, Minghui Tang, Meng Li, Miaojun Wang, Mingming Li, Ning Tian, Panpan Huang, Peng Zhang, Qiancheng Wang, Qinyu Chen, Qiushi Du, Ruiqi Ge, Ruisong Zhang, Ruizhe Pan, Runji Wang, R. J. Chen, R. L. Jin, Ruyi Chen, Shanghao Lu, Shangyan Zhou, Shanhuang Chen, Shengfeng Ye, Shiyu Wang, Shuiping Yu, Shunfeng Zhou, Shuting Pan, S. S. Li, Shuang Zhou, Shaoqing Wu, Shengfeng Ye, Tao Yun, Tian Pei, Tianyu Sun, T. Wang, Wangding Zeng, Wanjia Zhao, Wen Liu, Wenfeng Liang, Wenjun Gao, Wenqin Yu, Wentao Zhang, W. L. Xiao, Wei An, Xiaodong Liu, Xiaohan Wang, Xiaokang Chen, Xiaotao Nie, Xin Cheng, Xin Liu, Xin Xie, Xingchao Liu, Xinyu Yang, Xinyuan Li, Xuecheng Su, Xuheng Lin, X. Q. Li, Xiangyue Jin, Xiaojin Shen, Xiaosha Chen, Xiaowen Sun, Xiaoxiang Wang, Xinnan Song, Xinyi Zhou, Xianzu Wang, Xinxia Shan, Y. K. Li, Y. Q. Wang, Y. X. Wei, Yang Zhang, Yanhong Xu, Yao Li, Yao Zhao, Yaofeng Sun, Yaohui Wang, Yi Yu, Yichao Zhang, Yifan Shi, Yiliang Xiong, Ying He, Yishi Piao, Yisong Wang, Yixuan Tan, Yiyang Ma, Yiyuan Liu, Yongqiang Guo, Yuan Ou, Yuduan Wang, Yue Gong, Yuheng Zou, Yujia He, Yunfan Xiong, Yuxiang Luo, Yuxiang You, Yuxuan Liu, Yuyang Zhou, Y. X. Zhu, Yanhong Xu, Yanping Huang, Yaohui Li, Yi Zheng, Yuchen Zhu, Yunxian Ma, Ying Tang, Yukun Zha, Yuting Yan, Z. Z. Ren, Zehui Ren, Zhangli Sha, Zhe Fu, Zhean Xu, Zhenda Xie, Zhengyan Zhang, Zhewen Hao, Zhicheng Ma, Zhigang Yan, Zhiyu Wu, Zihui Gu, Zijia Zhu, Zijun Liu, Zilin Li, Ziwei Xie, Ziyang Song, Zizheng Pan, Zhen Huang, Zhipeng Xu, Zhongyu Zhang, and Zhen Zhang · 2025
Closest in time.
Mind the gap: A practical attack on GGUF quantization
Kazuki Egashira, Robin Staab, Mark Vero, Jingxuan He, and Martin Vechev · 2025
Closest in time.
NNsight and NDIF: Democratizing access to foundation model internals
Jaden Fried Fiotto-Kaufman, Alexander Russell Loftus, Eric Todd, Jannik Brinkmann, Koyena Pal, Dmitrii Troitskii, Michael Ripa, Adam Belfki, Can Rager, Caden Juang, Aaron Mueller, Samuel Marks, Arnab Sen Sharma, Francesca Lucchetti, Nikhil Prakash, Carla E. Brodley, Arjun Guha, Jonathan Bell, Byron C Wallace, and David Bau · 2025
Closest in time.
Freedom on the net 2024: China, 2024
Freedom House · 2025
Closest in time.
Ailuminate: Introducing v1.0 of the ai risk and reliability benchmark from mlcommons, 2025
Shaona Ghosh, Heather Frase, Adina Williams, Sarah Luger, Paul Röttger, Fazl Barez, Sean McGregor, Kenneth Fricklas, Mala Kumar, Quentin Feuillade-Montixi, Kurt Bollacker, Felix Friedrich, Ryan Tsang, Bertie Vidgen, Alicia Parrish, Chris Knotz, Eleonora Presani, Jonathan Bennion, Marisa Ferrara Boston, Mike Kuniavsky, Wiebke Hutiri, James Ezick, Malek Ben Salem, Rajat Sahay, Sujata Goswami, Usman Gohar, Ben Huang, Supheakmungkol Sarin, Elie Alhajjar, Canyu Chen, Roman Eng, Kashyap Ramanandula Manjusha, Virendra Mehta, Eileen Long, Murali Emani, Natan Vidra, Benjamin Rukundo, Abolfazl Shahbazi, Kongtao Chen, Rajat Ghosh, Vithursan Thangarasa, Pierre Peigné, Abhinav Singh, Max Bartolo, Satyapriya Krishna, Mubashara Akhtar, Rafael Gold, Cody Coleman, Luis Oala, Vassil Tashev, Joseph Marvin Imperial, Amy Russ, Sasidhar Kunapuli, Nicolas Miailhe, Julien Delaunay, Bhaktipriya Radharapu, Rajat Shinde, Tuesday, Debojyoti Dutta, Declan Grabb, Ananya Gangavarapu, Saurav Sahay, Agasthya Gangavarapu, Patrick Schramowski, Stephen Singam, Tom David, Xudong Han, Priyanka Mary Mammen, Tarunima Prabhakar, Venelin Kovatchev, Ahmed Ahmed, Kelvin N. Manyeki, Sandeep Madireddy, Foutse Khomh, Fedor Zhdanov, Joachim Baumann, Nina Vasan, Xianjun Yang, Carlos Mougn, Jibin Rajan Varghese, Hussain Chinoy, Seshakrishna Jitendar, Manil Maskey, Claire V. Hardgrove, Tianhao Li, Aakash Gupta, Emil Joswin, Yifan Mai, Shachi H Kumar, Cigdem Patlak, Kevin Lu, Vincent Alessi, Sree Bhargavi Balija, Chenhe Gu, Robert Sullivan, James Gealy, Matt Lavrisa, James Goel, Peter Mattson, Percy Liang, and Joaquin Vanschoren · 2025
Closest in time.
Endless jailbreaks with bijection learning, 2025
Brian R. Y. Huang, Maximilian Li, and Leonard Tang · 2025
Closest in time.
Auditing language models for hidden objectives, 2025
Samuel Marks, Johannes Treutlein, Trenton Bricken, Jack Lindsey, Jonathan Marcus, Siddharth Mishra-Sharma, Daniel Ziegler, Emmanuel Ameisen, Joshua Batson, Tim Belonax, Samuel R. Bowman, Shan Carter, Brian Chen, Hoagy Cunningham, Carson Denison, Florian Dietz, Satvik Golechha, Akbir Khan, Jan Kirchner, Jan Leike, Austin Meek, Kei Nishimura-Gasparian, Euan Ong, Christopher Olah, Adam Pearce, Fabien Roger, Jeanne Salle, Andy Shih, Meg Tong, Drake Thomas, Kelley Rivoire, Adam Jermyn, Monte MacDiarmid, Tom Henighan, and Evan Hubinger · 2025
Closest in time.
Openai gpt-4.5 system card
OpenAI · 2025
Closest in time.
Open-sourcing r1 1776, 2 2025
Perplexity AI · 2025
Closest in time.