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The advent of large language models (LLMs) has catalyzed a transformative shift in artificial intelligence, paving the way for advanced intelligent agents capable of sophisticated reasoning, robust perception, and versatile action across diverse domains.
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Facial expressions of emotion are not culturally universal
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Neural basis of reinforcement learning and decision making
Daeyeol Lee, Hyojung Seo, and Min Whan Jung · 2012
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Neural machine translation by jointly learning to align and translate
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Humans can discriminate more than 1 trillion olfactory stimuli
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Program synthesis with large language models
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Are NLP models really able to solve simple math word problems?
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Evaluating large language models trained on code
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Measuring coding challenge competence with APPS
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Did aristotle use a laptop? A question answering benchmark with implicit reasoning strategies
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Training verifiers to solve math word problems
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Lisa: Language models of isabelle proofs
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A diverse corpus for evaluating and developing english math word problem solvers
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Naturalproofs: Mathematical theorem proving in natural language
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Extracting training data from large language models
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Adversarial attacks on multi-agent communication
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Gps location spoofing attack detection for enhancing the security of autonomous vehicles
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Domain generalization using causal matching
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Cooperative and competitive biases for multi-agent reinforcement learning
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Donghee Shin · 2021
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Introducing chatgpt
OpenAI · 2022
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Zhifei Xie and Changqiao Wu · 2024
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Smart multiple photoresponsive tongue for sensing umami, sour and bitter tastes based on tb3+ functionalized hydrogen-bonded organic frameworks
Zishuo Zhang and Bing Yan · 2024
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Anyskin: Plug-and-play skin sensing for robotic touch
Raunaq Bhirangi, Venkatesh Pattabiraman, Enes Erciyes, Yifeng Cao, Tess Hellebrekers, and Lerrel Pinto · 2024
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Gama: A large audio-language model with advanced audio understanding and complex reasoning abilities
Sreyan Ghosh, Sonal Kumar, Ashish Seth, Chandra Kiran Reddy Evuru, Utkarsh Tyagi, S Sakshi, Oriol Nieto, Ramani Duraiswami, and Dinesh Manocha · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Gemini Team, Petko Georgiev, Ving Ian Lei, Ryan Burnell, Libin Bai, Anmol Gulati, Garrett Tanzer, Damien Vincent, Zhufeng Pan, Shibo Wang, et al · 2024
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Neuralfeels with neural fields: Visuotactile perception for in-hand manipulation
Sudharshan Suresh, Haozhi Qi, Tingfan Wu, Taosha Fan, Luis Pineda, Mike Lambeta, Jitendra Malik, Mrinal Kalakrishnan, Roberto Calandra, Michael Kaess, et al · 2024
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Posggym: A library for decision-theoretic planning and learning in partially observable, multi-agent environments
Jonathon Schwartz, Rhys Newbury, Dana Kulic, and Hanna Kurniawati · 2024
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The codec language model-based zero-shot spontaneous style tts system for covoc challenge 2024
Shuoyi Zhou, Yixuan Zhou, Weiqing Li, Jun Chen, Runchuan Ye, Weihao Wu, Zijian Lin, Shun Lei, and Zhiyong Wu · 2024
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Apollo: Band-sequence modeling for high-quality audio restoration
Kai Li and Yi Luo · 2024
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Visualwebarena: Evaluating multimodal agents on realistic visual web tasks
Jing Yu Koh, Robert Lo, Lawrence Jang, Vikram Duvvur, Ming Chong Lim, Po-Yu Huang, Graham Neubig, Shuyan Zhou, Ruslan Salakhutdinov, and Daniel Fried · 2024
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Spa-bench: A comprehensive benchmark for smartphone agent evaluation
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Androidworld: A dynamic benchmarking environment for autonomous agents
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Digitizing touch with an artificial multimodal fingertip
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A real-world webagent with planning, long context understanding, and program synthesis, 2024
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π 0 \pi_{0} : A vision-language-action flow model for general robot control
Kevin Black, Noah Brown, Danny Driess, Adnan Esmail, Michael Equi, Chelsea Finn, Niccolo Fusai, Lachy Groom, Karol Hausman, Brian Ichter, et al · 2024
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Rt-h: Action hierarchies using language
Suneel Belkhale, Tianli Ding, Ted Xiao, Pierre Sermanet, Quon Vuong, Jonathan Tompson, Yevgen Chebotar, Debidatta Dwibedi, and Dorsa Sadigh · 2024
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Kalm: Knowledgeable agents by offline reinforcement learning from large language model rollouts
Jing-Cheng Pang, Si-Hang Yang, Kaiyuan Li, Jiaji Zhang, Xiong-Hui Chen, Nan Tang, and Yang Yu · 2024
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Open x-embodiment: Robotic learning datasets and rt-x models: Open x-embodiment collaboration 0
Abby O’Neill, Abdul Rehman, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, et al · 2024
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Gorilla: Large language model connected with massive APIs
Shishir G Patil, Tianjun Zhang, Xin Wang, and Joseph E. Gonzalez · 2024
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Augmenting large language models with chemistry tools
Andres M. Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D. White, and Philippe Schwaller · 2024
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Sciagent: Tool-augmented language models for scientific reasoning
Yubo Ma, Zhibin Gou, Junheng Hao, Ruochen Xu, Shuohang Wang, Liangming Pan, Yujiu Yang, Yixin Cao, and Aixin Sun · 2024
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Tool learning with foundation models
Yujia Qin, Shengding Hu, Yankai Lin, Weize Chen, Ning Ding, Ganqu Cui, Zheni Zeng, Xuanhe Zhou, Yufei Huang, Chaojun Xiao, Chi Han, Yi Ren Fung, Yusheng Su, Huadong Wang, Cheng Qian, Runchu Tian, Kunlun Zhu, Shihao Liang, Xingyu Shen, Bokai Xu, Zhen Zhang, Yining Ye, Bowen Li, Ziwei Tang, Jing Yi, Yuzhang Zhu, Zhenning Dai, Lan Yan, Xin Cong, Yaxi Lu, Weilin Zhao, Yuxiang Huang, Junxi Yan, Xu Han, Xian Sun, Dahai Li, Jason Phang, Cheng Yang, Tongshuang Wu, Heng Ji, Guoliang Li, Zhiyuan Liu, and Maosong Sun · 2024
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A survey on large language model (llm) security and privacy: The good, the bad, and the ugly
Yifan Yao, Jinhao Duan, Kaidi Xu, Yuanfang Cai, Zhibo Sun, and Yue Zhang · 2024
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StraGo: Harnessing strategic guidance for prompt optimization
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Textgrad: Automatic “differentiation” via text
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Scaling monosemanticity: Extracting interpretable features from claude 3 sonnet
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Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers, September 2024
Chenglei Si, Diyi Yang, and Tatsunori Hashimoto · 2024
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SciAgents: Automating Scientific Discovery Through Bioinspired Multi-Agent Intelligent Graph Reasoning
Alireza Ghafarollahi and Markus J. Buehler · 2024
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Genesis: Towards the Automation of Systems Biology Research, September 2024
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ChemOS 2.0: An orchestration architecture for chemical self-driving laboratories
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Autonomous mobile robots for exploratory synthetic chemistry
Tianwei Dai, Sriram Vijayakrishnan, Filip T. Szczypiński, Jean-François Ayme, Ehsan Simaei, Thomas Fellowes, Rob Clowes, Lyubomir Kotopanov, Caitlin E. Shields, Zhengxue Zhou, John W. Ward, and Andrew I. Cooper · 2024
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Delocalized, asynchronous, closed-loop discovery of organic laser emitters
Felix Strieth-Kalthoff, Han Hao, Vandana Rathore, Joshua Derasp, Théophile Gaudin, Nicholas H. Angello, Martin Seifrid, Ekaterina Trushina, Mason Guy, Junliang Liu, Xun Tang, Masashi Mamada, Wesley Wang, Tuul Tsagaantsooj, Cyrille Lavigne, Robert Pollice, Tony C. Wu, Kazuhiro Hotta, Leticia Bodo, Shangyu Li, Mohammad Haddadnia, Agnieszka Wołos, Rafał Roszak, Cher Tian Ser, Carlota Bozal-Ginesta, Riley J. Hickman, Jenya Vestfrid, Andrés Aguilar-Granda, Elena L. Klimareva, Ralph C. Sigerson, Wenduan Hou, Daniel Gahler, Slawomir Lach, Adrian Warzybok, Oleg Borodin, Simon Rohrbach, Benjamin Sanchez-Lengeling, Chihaya Adachi, Bartosz A. Grzybowski, Leroy Cronin, Jason E. Hein, Martin D. Burke, and Alán Aspuru-Guzik · 2024
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The virtual lab: Ai agents design new sars-cov-2 nanobodies with experimental validation
Kyle Swanson, Wesley Wu, Nash L Bulaong, John E Pak, and James Zou · 2024
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Solving olympiad geometry without human demonstrations
Trieu H. Trinh, Yuhuai Wu, Quoc V. Le, He He, and Thang Luong · 2024
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Code generation with alphacodium: From prompt engineering to flow engineering
Tal Ridnik, Dedy Kredo, and Itamar Friedman · 2024
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Archon: An architecture search framework for inference-time techniques, 2024
Jon Saad-Falcon, Adrian Gamarra Lafuente, Shlok Natarajan, Nahum Maru, Hristo Todorov, Etash Guha, E. Kelly Buchanan, Mayee Chen, Neel Guha, Christopher Ré, and Azalia Mirhoseini · 2024
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Zhi Rui Tam, Cheng-Kuang Wu, Yi-Lin Tsai, Chieh-Yen Lin, Hung-yi Lee, and Yun-Nung Chen · 2024
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Optimizing instructions and demonstrations for multi-stage language model programs
Krista Opsahl-Ong, Michael J Ryan, Josh Purtell, David Broman, Christopher Potts, Matei Zaharia, and Omar Khattab · 2024
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PRompt optimization in multi-step tasks (PROMST): Integrating human feedback and heuristic-based sampling
Yongchao Chen, Jacob Arkin, Yilun Hao, Yang Zhang, Nicholas Roy, and Chuchu Fan · 2024
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Advprompter: Fast adaptive adversarial prompting for LLMs
Anselm Paulus, Arman Zharmagambetov, Chuan Guo, Brandon Amos, and Yuandong Tian · 2024
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Gemma scope: Open sparse autoencoders everywhere all at once on gemma 2
Tom Lieberum, Senthooran Rajamanoharan, Arthur Conmy, Lewis Smith, Nicolas Sonnerat, Vikrant Varma, János Kramár, Anca Dragan, Rohin Shah, and Neel Nanda · 2024
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Sparse feature circuits: Discovering and editing interpretable causal graphs in language models
Samuel Marks, Can Rager, Eric J Michaud, Yonatan Belinkov, David Bau, and Aaron Mueller · 2024
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Many-shot jailbreaking
Cem Anil, Esin Durmus, Nina Rimsky, Mrinank Sharma, Joe Benton, Sandipan Kundu, Joshua Batson, Meg Tong, Jesse Mu, Daniel J Ford, et al · 2024
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Evolve: Evaluating and optimizing LLMs for exploration
Allen Nie, Yi Su, Bo Chang, Jonathan N Lee, Ed H Chi, Quoc V Le, and Minmin Chen · 2024
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Can large language models explore in-context?
Akshay Krishnamurthy, Keegan Harris, Dylan J Foster, Cyril Zhang, and Aleksandrs Slivkins · 2024
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Llms are in-context reinforcement learners
Giovanni Monea, Antoine Bosselut, Kianté Brantley, and Yoav Artzi · 2024
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Aligning large language models via self-steering optimization
Hao Xiang, Bowen Yu, Hongyu Lin, Keming Lu, Yaojie Lu, Xianpei Han, Le Sun, Jingren Zhou, and Junyang Lin · 2024
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Epistemology
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ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models, April 2024
Jinheon Baek, Sujay Kumar Jauhar, Silviu Cucerzan, and Sung Ju Hwang · 2024
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The future of self-driving laboratories: From human in the loop interactive AI to gamification
Holland Hysmith, Elham Foadian, Shakti P. Padhy, Sergei V. Kalinin, Rob G. Moore, Olga S. Ovchinnikova, and Mahshid Ahmadi · 2024
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WorldAPIs: The World Is Worth How Many APIs? A Thought Experiment, July 2024
Jiefu Ou, Arda Uzunoglu, Benjamin Van Durme, and Daniel Khashabi · 2024
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AlabOS: A Python-based reconfigurable workflow management framework for autonomous laboratories
Yuxing Fei, Bernardus Rendy, Rishi Kumar, Olympia Dartsi, Hrushikesh P. Sahasrabuddhe, Matthew J. McDermott, Zheren Wang, Nathan J. Szymanski, Lauren N. Walters, David Milsted, Yan Zeng, Anubhav Jain, and Gerbrand Ceder · 2024
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CACTUS: Chemistry agent connecting tool usage to science
Andrew D McNaughton, Gautham Krishna Sankar Ramalaxmi, Agustin Kruel, Carter R Knutson, Rohith A Varikoti, and Neeraj Kumar · 2024
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Facile integration of robots into experimental orchestration at scientific user facilities
Chandima Fernando, Daniel Olds, Stuart I Campbell, and Phillip M Maffettone · 2024
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Review of low-cost self-driving laboratories in chemistry and materials science: The “frugal twin” concept
Stanley Lo, Sterling G Baird, Joshua Schrier, Ben Blaiszik, Nessa Carson, Ian Foster, Andrés Aguilar-Granda, Sergei V Kalinin, Benji Maruyama, Maria Politi, Helen Tran, Taylor D. Sparks, and Alan Aspuru-Guzik · 2024
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FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AI, December 2024
Elliot Glazer, Ege Erdil, Tamay Besiroglu, Diego Chicharro, Evan Chen, Alex Gunning, Caroline Falkman Olsson, Jean-Stanislas Denain, Anson Ho, Emily de Oliveira Santos, Olli Järviniemi, Matthew Barnett, Robert Sandler, Matej Vrzala, Jaime Sevilla, Qiuyu Ren, Elizabeth Pratt, Lionel Levine, Grant Barkley, Natalie Stewart, Bogdan Grechuk, Tetiana Grechuk, Shreepranav Varma Enugandla, and Mark Wildon · 2024
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H-ARC: A Robust Estimate of Human Performance on the Abstraction and Reasoning Corpus Benchmark, September 2024
Solim LeGris, Wai Keen Vong, Brenden M. Lake, and Todd M. Gureckis · 2024
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MedAgents: Large language models as collaborators for zero-shot medical reasoning
Xiangru Tang, Anni Zou, Zhuosheng Zhang, Ziming Li, Yilun Zhao, Xingyao Zhang, Arman Cohan, and Mark Gerstein · 2024
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VillagerAgent: A graph-based multi-agent framework for coordinating complex task dependencies in Minecraft
Yubo Dong, Xukun Zhu, Zhengzhe Pan, Linchao Zhu, and Yi Yang · 2024
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A scalable communication protocol for networks of large language models, 2024
Samuele Marro, Emanuele La Malfa, Jesse Wright, Guohao Li, Nigel Shadbolt, Michael Wooldridge, and Philip Torr · 2024
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Dittos: Personalized, embodied agents that participate in meetings when you are unavailable
Joanne Leong, John Tang, Edward Cutrell, Sasa Junuzovic, Gregory Paul Baribault, and Kori Inkpen · 2024
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Partnr: A benchmark for planning and reasoning in embodied multi-agent tasks, 2024
Matthew Chang, Gunjan Chhablani, Alexander Clegg, Mikael Dallaire Cote, Ruta Desai, Michal Hlavac, Vladimir Karashchuk, Jacob Krantz, Roozbeh Mottaghi, Priyam Parashar, Siddharth Patki, Ishita Prasad, Xavier Puig, Akshara Rai, Ram Ramrakhya, Daniel Tran, Joanne Truong, John M. Turner, Eric Undersander, and Tsung-Yen Yang · 2024
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Large language models playing mixed strategy nash equilibrium games
Alonso Silva · 2024
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States as strings as strategies: Steering language models with game-theoretic solvers
Ian Gemp, Yoram Bachrach, Marc Lanctot, Roma Patel, Vibhavari Dasagi, Luke Marris, Georgios Piliouras, Siqi Liu, and Karl Tuyls · 2024
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Measuring bargaining abilities of llms: A benchmark and a buyer-enhancement method
Tian Xia, Zhiwei He, Tong Ren, Yibo Miao, Zhuosheng Zhang, Yang Yang, and Rui Wang · 2024
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Simulating human strategic behavior: Comparing single and multi-agent llms
Karthik Sreedhar and Lydia Chilton · 2024
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Cooperate or collapse: Emergence of sustainable cooperation in a society of LLM agents
Giorgio Piatti, Zhijing Jin, Max Kleiman-Weiner, Bernhard Schölkopf, Mrinmaya Sachan, and Rada Mihalcea · 2024
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Silin Du and Xiaowei Zhang · 2024
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Agent-based modelling meets generative AI in social network simulations
Antonino Ferraro, Antonio Galli, Valerio La Gatta, Marco Postiglione, Gian Marco Orlando, Diego Russo, Giuseppe Riccio, Antonio Romano, and Vincenzo Moscato · 2024
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Project sid: Many-agent simulations toward AI civilization, 2024
Altera. AL, Andrew Ahn, Nic Becker, Stephanie Carroll, Nico Christie, Manuel Cortes, Arda Demirci, Melissa Du, Frankie Li, Shuying Luo, Peter Y Wang, Mathew Willows, Feitong Yang, and Guangyu Robert Yang · 2024
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Chartinsights: Evaluating multimodal large language models for low-level chart question answering
Yifan Wu, Lutao Yan, Leixian Shen, Yunhai Wang, Nan Tang, and Yuyu Luo · 2024
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Automl-agent: A multi-agent llm framework for full-pipeline automl
Patara Trirat, Wonyong Jeong, and Sung Ju Hwang · 2024
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Werewolf arena: A case study in LLM evaluation via social deduction
Suma Bailis, Jane Friedhoff, and Feiyang Chen · 2024
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Navigating complexity: Orchestrated problem solving with multi-agent llms, 2024
Sumedh Rasal and E. J. Hauer · 2024
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Yoichi Ishibashi and Yoshimasa Nishimura · 2024
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Traveler: A modular multi-lmm agent framework for video question-answering
Chuyi Shang, Amos You, Sanjay Subramanian, Trevor Darrell, and Roei Herzig · 2024
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Thread: Thinking deeper with recursive spawning
Philip Schroeder, Nathaniel Morgan, Hongyin Luo, and James Glass · 2024
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Llm multi-agent systems: Challenges and open problems
Shanshan Han, Qifan Zhang, Yuhang Yao, Weizhao Jin, Zhaozhuo Xu, and Chaoyang He · 2024
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Cultural evolution of cooperation among llm agents
Aron Vallinder and Edward Hughes · 2024
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Ethereum AI agent coordinator (EAAC): A framework for AI agent activity coordination
Taehoon Kim · 2024
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Advancing agentic systems: Dynamic task decomposition, tool integration and evaluation using novel metrics and dataset
Shankar Kumar Jeyakumar, Alaa Alameer Ahmad, and Adrian Garret Gabriel · 2024
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Nicer than humans: How do large language models behave in the prisoner’s dilemma?, 2024
Nicoló Fontana, Francesco Pierri, and Luca Maria Aiello · 2024
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A human-like reasoning framework for multi-phases planning task with large language models, 2024
Chengxing Xie and Difan Zou · 2024
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Yauwai Yim, Chunkit Chan, Tianyu Shi, Zheye Deng, Wei Fan, Tianshi Zheng, and Yangqiu Song · 2024
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Jailbreak attacks and defenses against large language models: A survey
Sibo Yi, Yule Liu, Zhen Sun, Tianshuo Cong, Xinlei He, Jiaxing Song, Ke Xu, and Qi Li · 2024
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Boosting jailbreak attack with momentum
Yihao Zhang and Zeming Wei · 2024
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Jailbreak instruction-tuned LLMs via end-of-sentence mlp re-weighting
Yifan Luo, Zhennan Zhou, Meitan Wang, and Bin Dong · 2024
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DROJ: A prompt-driven attack against large language models
Leyang Hu and Boran Wang · 2024
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Optimization-based prompt injection attack to LLM-as-a-judge
Jiawen Shi, Zenghui Yuan, Yinuo Liu, Yue Huang, Pan Zhou, Lichao Sun, and Neil Zhenqiang Gong · 2024
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Trust no ai: Prompt injection along the cia security triad
Johann Rehberger · 2024
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Subaru Kimura, Ryota Tanaka, Shumpei Miyawaki, Jun Suzuki, and Keisuke Sakaguchi · 2024
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Dataset and lessons learned from the 2024 satml LLM capture-the-flag competition
Edoardo Debenedetti, Javier Rando, Daniel Paleka, Silaghi Fineas Florin, Dragos Albastroiu, Niv Cohen, Yuval Lemberg, Reshmi Ghosh, Rui Wen, Ahmed Salem, et al · 2024
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Cody Clop and Yannick Teglia · 2024
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Prompt Infection: LLM-to-LLM Prompt Injection within Multi-Agent Systems
Donghyun Lee and Mo Tiwari · 2024
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Adversarial search engine optimization for large language models
Fredrik Nestaas, Edoardo Debenedetti, and Florian Tramèr · 2024
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Hallusionbench: an advanced diagnostic suite for entangled language hallucination and visual illusion in large vision-language models
Tianrui Guan, Fuxiao Liu, Xiyang Wu, Ruiqi Xian, Zongxia Li, Xiaoyu Liu, Xijun Wang, Lichang Chen, Furong Huang, Yaser Yacoob, et al · 2024
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Model merging and safety alignment: One bad model spoils the bunch
Hasan Abed Al Kader Hammoud, Umberto Michieli, Fabio Pizzati, Philip Torr, Adel Bibi, Bernard Ghanem, and Mete Ozay · 2024
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Poisoned chatgpt finds work for idle hands: Exploring developers’ coding practices with insecure suggestions from poisoned ai models
Sanghak Oh, Kiho Lee, Seonhye Park, Doowon Kim, and Hyoungshick Kim · 2024
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Secret collusion among generative AI agents
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Exploiting the vulnerability of large language models via defense-aware architectural backdoor
Abdullah Arafat Miah and Yu Bi · 2024
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Scaling laws for data poisoning in LLMs
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Best-of-venom: Attacking rlhf by injecting poisoned preference data
Tim Baumgärtner, Yang Gao, Dana Alon, and Donald Metzler · 2024
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Sleeper agents: Training deceptive LLMs that persist through safety training
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Exploring backdoor attacks against large language model-based decision making
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Backdooring instruction-tuned large language models with virtual prompt injection
Jun Yan, Vikas Yadav, Shiyang Li, Lichang Chen, Zheng Tang, Hai Wang, Vijay Srinivasan, Xiang Ren, and Hongxia Jin · 2024
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Stealing part of a production language model
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Towards more realistic extraction attacks: An adversarial perspective
Yash More, Prakhar Ganesh, and Golnoosh Farnadi · 2024
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Pleak: Prompt leaking attacks against large language model applications
Bo Hui, Haolin Yuan, Neil Gong, Philippe Burlina, and Yinzhi Cao · 2024
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Itay Yona, Ilia Shumailov, Jamie Hayes, and Nicholas Carlini · 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
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Jailbreaking and mitigation of vulnerabilities in large language models
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Embedding-based classifiers can detect prompt injection attacks
Md Ahsan Ayub and Subhabrata Majumdar · 2024
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Attention tracker: Detecting prompt injection attacks in llms
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Seven failure points when engineering a retrieval augmented generation system
Scott Barnett, Stefanus Kurniawan, Srikanth Thudumu, Zach Brannelly, and Mohamed Abdelrazek · 2024
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Uncertainty-based abstention in LLMs improves safety and reduces hallucinations
Christian Tomani, Kamalika Chaudhuri, Ivan Evtimov, Daniel Cremers, and Mark Ibrahim · 2024
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Detecting hallucinations in large language model generation: A token probability approach
Ernesto Quevedo, Jorge Yero, Rachel Koerner, Pablo Rivas, and Tomas Cerny · 2024
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Kaifeng Lyu, Haoyu Zhao, Xinran Gu, Dingli Yu, Anirudh Goyal, and Sanjeev Arora · 2024
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Are you still on track!? catching LLM task drift with activations
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Mind the privacy unit! user-level differential privacy for language model fine-tuning
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Federatedscope-llm: A comprehensive package for fine-tuning large language models in federated learning
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Encryption-friendly LLM architecture
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SafeGen: Mitigating Sexually Explicit Content Generation in Text-to-Image Models
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Large language models can be good privacy protection learners
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Jatmo: Prompt injection defense by task-specific finetuning
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Revisiting character-level adversarial attacks for language models
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Legilimens: Practical and unified content moderation for large language model services
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Hannah Brown, Leon Lin, Kenji Kawaguchi, and Michael Shieh · 2024
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Adversarial text purification: A large language model approach for defense
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Diffender: Diffusion-based adversarial defense against patch attacks
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A survey on adversarial robustness of lidar-based machine learning perception in autonomous vehicles
Junae Kim and Amardeep Kaur · 2024
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Bias and fairness in large language models: A survey
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Modeling opinion misperception and the emergence of silence in online social system
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Speechguard: Exploring the adversarial robustness of multimodal large language models
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A survey of wireless sensing security from a role-based view: Victim, weapon, and shield
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Sensor-based iot data privacy protection
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Diversinet: Mitigating bias in deep classification networks across sensitive attributes through diffusion-generated data
Basudha Pal, Aniket Roy, Ram Prabhakar Kathirvel, Alice J O’Toole, and Rama Chellappa · 2024
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Error-driven uncertainty aware training
Pedro Mendes, Paolo Romano, and David Garlan · 2024
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Defending against indirect prompt injection attacks with spotlighting
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Confusedpilot: Confused deputy risks in rag-based llms
Ayush RoyChowdhury, Mulong Luo, Prateek Sahu, Sarbartha Banerjee, and Mohit Tiwari · 2024
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Poisonedrag: Knowledge corruption attacks to retrieval-augmented generation of large language models
Wei Zou, Runpeng Geng, Binghui Wang, and Jinyuan Jia · 2024
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Machine against the rag: Jamming retrieval-augmented generation with blocker documents
Avital Shafran, Roei Schuster, and Vitaly Shmatikov · 2024
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Badrag: Identifying vulnerabilities in retrieval augmented generation of large language models
Jiaqi Xue, Mengxin Zheng, Yebowen Hu, Fei Liu, Xun Chen, and Qian Lou · 2024
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Whispers in grammars: Injecting covert backdoors to compromise dense retrieval systems
Quanyu Long, Yue Deng, LeiLei Gan, Wenya Wang, and Sinno Jialin Pan · 2024
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Demystifying rce vulnerabilities in llm-integrated apps
Tong Liu, Zizhuang Deng, Guozhu Meng, Yuekang Li, and Kai Chen · 2024
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Coercing LLMs to do and reveal (almost) anything
Jonas Geiping, Alex Stein, Manli Shu, Khalid Saifullah, Yuxin Wen, and Tom Goldstein · 2024
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Eia: Environmental injection attack on generalist web agents for privacy leakage
Zeyi Liao, Lingbo Mo, Chejian Xu, Mintong Kang, Jiawei Zhang, Chaowei Xiao, Yuan Tian, Bo Li, and Huan Sun · 2024
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Foundational challenges in assuring alignment and safety of large language models
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Taming overconfidence in llms: Reward calibration in rlhf
Jixuan Leng, Chengsong Huang, Banghua Zhu, and Jiaxin Huang · 2024
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Managing extreme ai risks amid rapid progress
Yoshua Bengio, Geoffrey Hinton, Andrew Yao, Dawn Song, Pieter Abbeel, Trevor Darrell, Yuval Noah Harari, Ya-Qin Zhang, Lan Xue, Shai Shalev-Shwartz, et al · 2024
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Safebench: A safety evaluation framework for multimodal large language models
Zonghao Ying, Aishan Liu, Siyuan Liang, Lei Huang, Jinyang Guo, Wenbo Zhou, Xianglong Liu, and Dacheng Tao · 2024
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Alignment with preference optimization is all you need for LLM safety
Reda Alami, Ali Khalifa Almansoori, Ahmed Alzubaidi, Mohamed El Amine Seddik, Mugariya Farooq, and Hakim Hacid · 2024
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Towards safety and helpfulness balanced responses via controllable large language models
Yi-Lin Tuan, Xilun Chen, Eric Michael Smith, Louis Martin, Soumya Batra, Asli Celikyilmaz, William Yang Wang, and Daniel M Bikel · 2024
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Provably robust dpo: Aligning language models with noisy feedback
Sayak Ray Chowdhury, Anush Kini, and Nagarajan Natarajan · 2024
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Towards AI-45 ∘ law: A roadmap to trustworthy AGI
Yang Chao, Lu Chaochao, Wang Yingchun, and Zhou Bowen · 2024
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LLM Leaderboard - Compare GPT-4o, Llama 3, Mistral, Gemini & other models, 2024
Artificial Analysis · 2024
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Clémentine Fourrier, Nathan Habib, Alina Lozovskaya, Konrad Szafer, and Thomas Wolf · 2024
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A survey on trustworthy llm agents: Threats and countermeasures
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Cogvlm: Visual expert for pretrained language models
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Training agents by reinforcing reasoning, 2025
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Physics reasoner: Knowledge-augmented reasoning for solving physics problems with large language models
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Deepseek-r1: Incentivizing reasoning capability in LLMs via reinforcement learning
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Hao Peng, Yunjia Qi, Xiaozhi Wang, Zijun Yao, Bin Xu, Lei Hou, and Juanzi Li · 2025
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rstar-math: Small LLMs can master math reasoning with self-evolved deep thinking, 2025
Xinyu Guan, Li Lyna Zhang, Yifei Liu, Ning Shang, Youran Sun, Yi Zhu, Fan Yang, and Mao Yang · 2025
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Atom of thoughts for markov llm test-time scaling, 2025
Fengwei Teng, Zhaoyang Yu, Quan Shi, Jiayi Zhang, Chenglin Wu, and Yuyu Luo · 2025
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Scaling test-time compute without verification or rl is suboptimal
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Unified mind model: Reimagining autonomous agents in the llm era
Pengbo Hu and Xiang Ying · 2025
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Understanding long videos via llm-powered entity relation graphs
Meng Chu, Yicong Li, and Tat-Seng Chua · 2025
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A large language model for advanced power dispatch
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Simpo: Simple preference optimization with a reference-free reward
Yu Meng, Mengzhou Xia, and Danqi Chen · 2025
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An opponent striatal circuit for distributional reinforcement learning
Adam S Lowet, Qiao Zheng, Melissa Meng, Sara Matias, Jan Drugowitsch, and Naoshige Uchida · 2025
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Emotional ai: Privacy, manipulation, and bias risks, 2024a
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Emotional artificial intelligence: Risks and opportunities, 2024b
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Prakhar Bhardwaj, Sheethal Bhat, and Andreas Maier · 2025
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The brain’s action-mode network
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Universal actions for enhanced embodied foundation models
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Training agents by reinforcing reasoning, 2025
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From decision to action in surgical autonomy: Multi-modal large language models for robot-assisted blood suction
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Agent laboratory: Using LLM agents as research assistants
Samuel Schmidgall, Yusheng Su, Ze Wang, Ximeng Sun, Jialian Wu, Xiaodong Yu, Jiang Liu, Zicheng Liu, and Emad Barsoum · 2025
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ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning, January 2025
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Towards an AI co-scientist, February 2025
Juraj Gottweis, Wei-Hung Weng, Alexander Daryin, Tao Tu, Anil Palepu, Petar Sirkovic, Artiom Myaskovsky, Felix Weissenberger, Keran Rong, Ryutaro Tanno, Khaled Saab, Dan Popovici, Jacob Blum, Fan Zhang, Katherine Chou, Avinatan Hassidim, Burak Gokturk, Amin Vahdat, Pushmeet Kohli, Yossi Matias, Andrew Carroll, Kavita Kulkarni, Nenad Tomasev, Yuan Guan, Vikram Dhillon, Eeshit Dhaval Vaishnav, Byron Lee, Tiago R. D. Costa, José R. Penadés, Gary Peltz, Yunhan Xu, Annalisa Pawlosky, Alan Karthikesalingam, and Vivek Natarajan · 2025
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Self-supervised prompt optimization
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Openai o3-mini system card, 2025
OpenAI · 2025
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Superintelligent Agents Pose Catastrophic Risks: Can Scientist AI Offer a Safer Path?, February 2025
Yoshua Bengio, Michael Cohen, Damiano Fornasiere, Joumana Ghosn, Pietro Greiner, Matt MacDermott, Sören Mindermann, Adam Oberman, Jesse Richardson, Oliver Richardson, Marc-Antoine Rondeau, Pierre-Luc St-Charles, and David Williams-King · 2025
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Protein large language models: A comprehensive survey
Yijia Xiao, Wanjia Zhao, Junkai Zhang, Yiqiao Jin, Han Zhang, Zhicheng Ren, Renliang Sun, Haixin Wang, Guancheng Wan, Pan Lu, et al · 2025
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ECL Documentation
Emerald Cloud Lab · 2025
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Agency Is Frame-Dependent, February 2025
David Abel, André Barreto, Michael Bowling, Will Dabney, Shi Dong, Steven Hansen, Anna Harutyunyan, Khimya Khetarpal, Clare Lyle, Razvan Pascanu, Georgios Piliouras, Doina Precup, Jonathan Richens, Mark Rowland, Tom Schaul, and Satinder Singh · 2025
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DOGE: Reforming AI Conferences and Towards a Future Civilization of Fairness and Justice, February 2025
Zeyuan Allen-Zhu and Xiaoli Xu · 2025
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EAIRA: Establishing a methodology for evaluating AI models as scientific research assistants
Franck Cappello, Sandeep Madireddy, Robert Underwood, Neil Getty, Nicholas Lee-Ping Chia, Nesar Ramachandra, Josh Nguyen, Murat Keceli, Tanwi Mallick, Zilinghan Li, Marieme Ngom, Chenhui Zhangx, Angel Yanguas-Gilxi, Evan Antoniuk, Bhavya Kailkhura, Minyang Tian, Yufeng Du, Yuan-Sen Ting, Azton Wells, Bogdan Nicolae, Avinash Maurya, M. Mustafa Rafique, Eliu Huerta, Bo Li, Ian Foster, and Rick Stevens · 2025
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Introducing deep research
OpenAI · 2025
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Human-in-the-loop software development agents, 2025
Wannita Takerngsaksiri, Jirat Pasuksmit, Patanamon Thongtanunam, Chakkrit Tantithamthavorn, Ruixiong Zhang, Fan Jiang, Jing Li, Evan Cook, Kun Chen, and Ming Wu · 2025
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Model context protocol, 2025
Anthropic · 2025
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Collab-overcooked: Benchmarking and evaluating large language models as collaborative agents, 2025
Haochen Sun, Shuwen Zhang, Lei Ren, Hao Xu, Hao Fu, Caixia Yuan, and Xiaojie Wang · 2025
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Realm-bench: A real-world planning benchmark for llms and multi-agent systems, 2025
Longling Geng and Edward Y. Chang · 2025
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Multi-agent collaboration mechanisms: A survey of llms
Khanh-Tung Tran, Dung Dao, Minh-Duong Nguyen, Quoc-Viet Pham, Barry O’Sullivan, and Hoang D Nguyen · 2025
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Budgetmlagent: A cost-effective llm multi-agent system for automating machine learning tasks, 2025
Shubham Gandhi, Manasi Patwardhan, Lovekesh Vig, and Gautam Shroff · 2025
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Karma: Leveraging multi-agent llms for automated knowledge graph enrichment, 2025
Yuxing Lu and Jinzhuo Wang · 2025
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Agentnetworkprotocol, 2025
Gaowei Chang · 2025
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Master: A multi-agent system with llm specialized mcts, 2025
Bingzheng Gan, Yufan Zhao, Tianyi Zhang, Jing Huang, Yusu Li, Shu Xian Teo, Changwang Zhang, and Wei Shi · 2025
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Hanqing Yang, Jingdi Chen, Marie Siew, Tania Lorido-Botran, and Carlee Joe-Wong · 2025
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Flow: A modular approach to automated agentic workflow generation
Boye Niu, Yiliao Song, Kai Lian, Yifan Shen, Yu Yao, Kun Zhang, and Tongliang Liu · 2025
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Jinghua Piao, Yuwei Yan, Jun Zhang, Nian Li, Junbo Yan, Xiaochong Lan, Zhihong Lu, Zhiheng Zheng, Jing Yi Wang, Di Zhou, Chen Gao, Fengli Xu, Fang Zhang, Ke Rong, Jun Su, and Yong Li · 2025
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Cooperate or collapse: Emergence of sustainable cooperation in a society of llm agents
Giorgio Piatti, Zhijing Jin, Max Kleiman-Weiner, Bernhard Schölkopf, Mrinmaya Sachan, and Rada Mihalcea · 2025
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Collaborative gym: A framework for enabling and evaluating human-agent collaboration, 2025
Yijia Shao, Vinay Samuel, Yucheng Jiang, John Yang, and Diyi Yang · 2025
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Multiagent finetuning: Self improvement with diverse reasoning chains
Vighnesh Subramaniam, Yilun Du, Joshua B Tenenbaum, Antonio Torralba, Shuang Li, and Igor Mordatch · 2025
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Building math agents with multi-turn iterative preference learning, 2025
Wei Xiong, Chengshuai Shi, Jiaming Shen, Aviv Rosenberg, Zhen Qin, Daniele Calandriello, Misha Khalman, Rishabh Joshi, Bilal Piot, Mohammad Saleh, Chi Jin, Tong Zhang, and Tianqi Liu · 2025
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Raconteur: A knowledgeable, insightful, and portable llm-powered shell command explainer
Jiangyi Deng, Xinfeng Li, Yanjiao Chen, Yijie Bai, Haiqin Weng, Yan Liu, Tao Wei, and Wenyuan Xu · 2025
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Comma: A communicative multimodal multi-agent benchmark, 2025
Timothy Ossowski, Jixuan Chen, Danyal Maqbool, Zefan Cai, Tyler Bradshaw, and Junjie Hu · 2025
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Graph of ai ideas: Leveraging knowledge graphs and llms for ai research idea generation, 2025
Xian Gao, Zongyun Zhang, Mingye Xie, Ting Liu, and Yuzhuo Fu · 2025
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Pokerbench: Training large language models to become professional poker players, 2025
Richard Zhuang, Akshat Gupta, Richard Yang, Aniket Rahane, Zhengyu Li, and Gopala Anumanchipalli · 2025
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Human simulacra: Benchmarking the personification of large language models, 2025
Qiuejie Xie, Qiming Feng, Tianqi Zhang, Qingqiu Li, Linyi Yang, Yuejie Zhang, Rui Feng, Liang He, Shang Gao, and Yue Zhang · 2025
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On the resilience of llm-based multi-agent collaboration with faulty agents, 2025
Jen tse Huang, Jiaxu Zhou, Tailin Jin, Xuhui Zhou, Zixi Chen, Wenxuan Wang, Youliang Yuan, Michael R. Lyu, and Maarten Sap · 2025
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Fatemeh Nazary, Yashar Deldjoo, and Tommaso di Noia · 2025
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Probe before you talk: Towards black-box defense against backdoor unalignment for large language models
Biao Yi, Tiansheng Huang, Sishuo Chen, Tong Li, Zheli Liu, Chu Zhixuan, and Yiming Li · 2025
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Towards label-only membership inference attack against pre-trained large language models
Yu He, Boheng Li, Liu Liu, Zhongjie Ba, Wei Dong, Yiming Li, Zhan Qin, Kui Ren, and Chun Chen · 2025
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Junyuan Mao, Fanci Meng, Yifan Duan, Miao Yu, Xiaojun Jia, Junfeng Fang, Yuxuan Liang, Kun Wang, and Qingsong Wen · 2025
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Anyedit: Edit any knowledge encoded in language models
Houcheng Jiang, Junfeng Fang, Ningyu Zhang, Guojun Ma, Mingyang Wan, Xiang Wang, Xiangnan He, and Tat-seng Chua · 2025
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Xiaojun Jia, Sensen Gao, Simeng Qin, Ke Ma, Xinfeng Li, Yihao Huang, Wei Dong, Yang Liu, and Xiaochun Cao · 2025
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Multi-agent risks from advanced ai
Lewis Hammond, Alan Chan, Jesse Clifton, Jason Hoelscher-Obermaier, Akbir Khan, Euan McLean, Chandler Smith, Wolfram Barfuss, Jakob Foerster, Tomáš Gavenčiak, et al · 2025
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Introducing superalignment
OpenAI · 2025
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Humans monitor learning progress in curiosity-driven exploration
Alexandr Ten, Pramod Kaushik, Pierre-Yves Oudeyer, and Jacqueline Gottlieb · 2041
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Opportunities for retrieval and tool augmented large language models in scientific facilities
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