Key papers

• Zephyr: Direct Distillation Of LM Alignment (2023)
  Lewis Tunstall, Edward Beeching, Nathan Lambert, et al.
  38.56
• Training Language Models To Follow Instructions With Human Feedback (2022)
  Long Ouyang, Jeff Wu, Xu Jiang, et al.
  36.92
• BLOOM: A 176B-Parameter Open-Access Multilingual Language Model (2022)
  BigScience Workshop: Teven Le Scao, Angela Fan, Christopher Akiki, et al.
  33.79
• Step-dpo: Step-wise Preference Optimization For Long-chain Reasoning Of Llms (2024)
  Xin Lai, Zhuotao Tian, Yukang Chen, et al.
  31.31
• Chatbot Arena: An Open Platform For Evaluating Llms By Human Preference (2024)
  Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, et al.
  31.16
• Magpie: Alignment Data Synthesis From Scratch By Prompting Aligned Llms With Nothing (2024)
  Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.
  28.04
• Trustworthy Llms: A Survey And Guideline For Evaluating Large Language Models' Alignment (2023)
  Yang Liu, Yuanshun Yao, Jean-Francois Ton, et al.
  27.94
• Ultrafeedback: Boosting Language Models With Scaled AI Feedback (2023)
  Ganqu Cui, Lifan Yuan, Ning Ding, et al.
  27.73
• Chain-of-verification Reduces Hallucination In Large Language Models (2023)
  Shehzaad Dhuliawala, Mojtaba Komeili, Jing Xu, et al.
  27.71
• Is DPO Superior To PPO For LLM Alignment? A Comprehensive Study (2024)
  Shusheng Xu, Wei Fu, Jiaxuan Gao, et al.
  27.53
• Gsm-symbolic: Understanding The Limitations Of Mathematical Reasoning In Large Language Models (2024)
  Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.
  27.04
• Longalign: A Recipe For Long Context Alignment Of Large Language Models (2024)
  Yushi Bai, Xin Lv, Jiajie Zhang, et al.
  26.93
• Evaluating Large Language Models: A Comprehensive Survey (2023)
  Zishan Guo, Renren Jin, Chuang Liu, et al.
  26.82
• Direct Nash Optimization: Teaching Language Models To Self-improve With General Preferences (2024)
  Corby Rosset, Ching-An Cheng, Arindam Mitra, et al.
  25.73
• Llms Know More Than They Show: On The Intrinsic Representation Of LLM Hallucinations (2024)
  Hadas Orgad, Michael Toker, Zorik Gekhman, et al.
  25.38
• Teaching Large Language Models To Reason With Reinforcement Learning (2024)
  Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, et al.
  25.08
• Detoxifying Large Language Models Via Knowledge Editing (2024)
  Mengru Wang, Ningyu Zhang, Ziwen Xu, et al.
  25.02
• Judging The Judges: Evaluating Alignment And Vulnerabilities In Llms-as-judges (2024)
  Aman Singh Thakur, Kartik Choudhary, Venkat Srinik Ramayapally, et al.
  24.88
• Toward Self-improvement Of Llms Via Imagination, Searching, And Criticizing (2024)
  Ye Tian, Baolin Peng, Linfeng Song, et al.
  24.80
• Siren's Song In The AI Ocean: A Survey On Hallucination In Large Language Models (2023)
  Yue Zhang, Yafu Li, Leyang Cui, et al.
  24.78
• Salad-bench: A Hierarchical And Comprehensive Safety Benchmark For Large Language Models (2024)
  Lijun Li, Bowen Dong, Ruohui Wang, et al.
  24.45
• From Crowdsourced Data To High-quality Benchmarks: Arena-hard And Benchbuilder Pipeline (2024)
  Tianle Li, Wei-Lin Chiang, Evan Frick, et al.
  24.39
• Injecagent: Benchmarking Indirect Prompt Injections In Tool-integrated Large Language Model Agents (2024)
  Qiusi Zhan, Zhixiang Liang, Zifan Ying, et al.
  24.31
• A Wolf In Sheep's Clothing: Generalized Nested Jailbreak Prompts Can Fool Large Language Models Easily (2023)
  Peng Ding, Jun Kuang, Dan Ma, et al.
  24.05
• Patchscopes: A Unifying Framework For Inspecting Hidden Representations Of Language Models (2024)
  Asma Ghandeharioun, Avi Caciularu, Adam Pearce, et al.
  23.87
• Black-box Prompt Optimization: Aligning Large Language Models Without Model Training (2023)
  Jiale Cheng, Xiao Liu, Kehan Zheng, et al.
  23.78
• Jailbreaking Black Box Large Language Models In Twenty Queries (2023)
  Patrick Chao, Alexander Robey, Edgar Dobriban, et al.
  23.49
• You Only Look At Screens: Multimodal Chain-of-action Agents (2023)
  Zhuosheng Zhang, Aston Zhang
  23.42
• "do Anything Now": Characterizing And Evaluating In-the-wild Jailbreak Prompts On Large Language Models (2023)
  Xinyue Shen, Zeyuan Chen, Michael Backes, et al.
  23.21
• Dyval: Dynamic Evaluation Of Large Language Models For Reasoning Tasks (2023)
  Kaijie Zhu, Jiaao Chen, Jindong Wang, et al.
  23.15
• Autodan: Generating Stealthy Jailbreak Prompts On Aligned Large Language Models (2023)
  Xiaogeng Liu, Nan Xu, Muhao Chen, et al.
  22.91
• Cold-attack: Jailbreaking Llms With Stealthiness And Controllability (2024)
  Xingang Guo, Fangxu Yu, Huan Zhang, et al.
  22.77
• Reinforced Self-training (rest) For Language Modeling (2023)
  Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, et al.
  22.75
• A Comprehensive Survey Of Hallucination Mitigation Techniques In Large Language Models (2024)
  S. M Towhidul Islam Tonmoy, S M Mehedi Zaman, Vinija Jain, et al.
  22.74
• Quantifying Language Models' Sensitivity To Spurious Features In Prompt Design Or: How I Learned To Start Worrying About Prompt Formatting (2023)
  Melanie Sclar, Yejin Choi, Yulia Tsvetkov, et al.
  22.72
• Reasoning On Graphs: Faithful And Interpretable Large Language Model Reasoning (2023)
  Linhao Luo, Yuan-Fang Li, Gholamreza Haffari, et al.
  22.59
• Ovis: Structural Embedding Alignment For Multimodal Large Language Model (2024)
  Shiyin Lu, Yang Li, Qing-Guo Chen, et al.
  22.55
• Alpacare:instruction-tuned Large Language Models For Medical Application (2023)
  Xinlu Zhang, Chenxin Tian, Xianjun Yang, et al.
  22.41
• Does Fine-tuning Llms On New Knowledge Encourage Hallucinations? (2024)
  Zorik Gekhman, Gal Yona, Roee Aharoni, et al.
  22.36
• WISE: Rethinking The Knowledge Memory For Lifelong Model Editing Of Large Language Models (2024)
  Peng Wang, Zexi Li, Ningyu Zhang, et al.
  22.31
• LLM Evaluators Recognize And Favor Their Own Generations (2024)
  Arjun Panickssery, Samuel R. Bowman, Shi Feng
  22.26
• AMBER: An Llm-free Multi-dimensional Benchmark For Mllms Hallucination Evaluation (2023)
  Junyang Wang, Yuhang Wang, Guohai Xu, et al.
  22.17
• Certifying LLM Safety Against Adversarial Prompting (2023)
  Aounon Kumar, Chirag Agarwal, Suraj Srinivas, et al.
  22.14
• Ragtruth: A Hallucination Corpus For Developing Trustworthy Retrieval-augmented Language Models (2024)
  Cheng Niu, Yuanhao Wu, Juno Zhu, et al.
  22.10
• R-tuning: Instructing Large Language Models To Say `I Don't Know' (2023)
  Hanning Zhang, Shizhe Diao, Yong Lin, et al.
  21.96
• Explainability For Large Language Models: A Survey (2023)
  Haiyan Zhao, Hanjie Chen, Fan Yang, et al.
  21.79
• Safedecoding: Defending Against Jailbreak Attacks Via Safety-aware Decoding (2024)
  Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.
  21.73
• The Geometry Of Truth: Emergent Linear Structure In Large Language Model Representations Of True/false Datasets (2023)
  Samuel Marks, Max Tegmark
  21.67
• Shadow Alignment: The Ease Of Subverting Safely-aligned Language Models (2023)
  Xianjun Yang, Xiao Wang, Qi Zhang, et al.
  21.39
• Large Language Models In Medicine: The Potentials And Pitfalls (2023)
  Jesutofunmi A. Omiye, Haiwen Gui, Shawheen J. Rezaei, et al.
  21.25
• Understanding The Effects Of RLHF On LLM Generalisation And Diversity (2023)
  Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis, et al.
  21.24
• R-judge: Benchmarking Safety Risk Awareness For LLM Agents (2024)
  Tongxin Yuan, Zhiwei He, Lingzhong Dong, et al.
  21.20
• Usable XAI: 10 Strategies Towards Exploiting Explainability In The LLM Era (2024)
  Xuansheng Wu, Haiyan Zhao, Yaochen Zhu, et al.
  21.19
• Anchored Preference Optimization And Contrastive Revisions: Addressing Underspecification In Alignment (2024)
  Karel D'Oosterlinck, Winnie Xu, Chris Develder, et al.
  21.08
• Rethinking Machine Unlearning For Large Language Models (2024)
  Sijia Liu, Yuanshun Yao, Jinghan Jia, et al.
  21.08
• Negative Preference Optimization: From Catastrophic Collapse To Effective Unlearning (2024)
  Ruiqi Zhang, Licong Lin, Yu Bai, et al.
  20.98
• Alignbench: Benchmarking Chinese Alignment Of Large Language Models (2023)
  Xiao Liu, Xuanyu Lei, Shengyuan Wang, et al.
  20.90
• Smaug: Fixing Failure Modes Of Preference Optimisation With Dpo-positive (2024)
  Arka Pal, Deep Karkhanis, Samuel Dooley, et al.
  20.86
• Tree Of Attacks: Jailbreaking Black-box Llms Automatically (2023)
  Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, et al.
  20.80
• GPTFUZZER: Red Teaming Large Language Models With Auto-generated Jailbreak Prompts (2023)
  Jiahao Yu, Xingwei Lin, Zheng Yu, et al.
  20.73