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We present MultiChallenge, a pioneering benchmark evaluating large language models (LLMs) on conducting multi-turn conversations with human users, a crucial yet underexamined capability for their applications.
Discovering language model behaviors with model-written evaluations
Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, Karina Nguyen, Edwin Chen, Scott Heiner, Craig Pettit, Catherine Olsson, Sandipan Kundu, Saurav Kadavath, et al. 2022 · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023
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Are you sure? challenging llms leads to performance drops in the flipflop experiment
Philippe Laban, Lidiya Murakhovs’ ka, Caiming Xiong, and Chien-Sheng Wu. 2023 · 2023
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Agentbench: Evaluating llms as agents
Xiao Liu, Hao Yu, Hanchen Zhang, Yifan Xu, Xuanyu Lei, Hanyu Lai, Yu Gu, Hangliang Ding, Kaiwen Men, Kejuan Yang, et al. 2023 · 2023
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Towards understanding sycophancy in language models
Mrinank Sharma, Meg Tong, Tomasz Korbak, David Duvenaud, Amanda Askell, Samuel R Bowman, Newton Cheng, Esin Durmus, Zac Hatfield-Dodds, Scott R Johnston, et al. 2023 · 2023
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Mint: Evaluating llms in multi-turn interaction with tools and language feedback
Xingyao Wang, Zihan Wang, Jiateng Liu, Yangyi Chen, Lifan Yuan, Hao Peng, and Heng Ji. 2023 · 2023
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Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, et al. 2023 · 2023
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Instruction-following evaluation for large language models
Jeffrey Zhou, Tianjian Lu, Swaroop Mishra, Siddhartha Brahma, Sujoy Basu, Yi Luan, Denny Zhou, and Le Hou. 2023 · 2023
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Through the lens of core competency: Survey on evaluation of large language models
Zhuang Ziyu, Chen Qiguang, Ma Longxuan, Li Mingda, Han Yi, Qian Yushan, Bai Haopeng, Zhang Weinan, and Ting Liu. 2023 · 2023
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Prompt leakage effect and mitigation strategies for multi-turn llm applications
Divyansh Agarwal, Alexander Richard Fabbri, Ben Risher, Philippe Laban, Shafiq Joty, and Chien-Sheng Wu. 2024 · 2024
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The claude 3 model family: Opus, sonnet, haiku
AI Anthropic. 2024 · 2024
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Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al. 2024 · 2024
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Scaling synthetic data creation with 1,000,000,000 personas
Tao Ge, Xin Chan, Xiaoyang Wang, Dian Yu, Haitao Mi, and Dong Yu. 2024 · 2024
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Frontiermath: A benchmark for evaluating advanced mathematical reasoning in ai
Elliot Glazer, Ege Erdil, Tamay Besiroglu, Diego Chicharro, Evan Chen, Alex Gunning, Caroline Falkman Olsson, Jean-Stanislas Denain, Anson Ho, Emily de Oliveira Santos, et al. 2024 · 2024
Cited alongside, same era.
Multi-if: Benchmarking llms on multi-turn and multilingual instructions following
Au Large — mistral.ai
Mistral AI. 2024 · 2024
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Agentinstruct: Toward generative teaching with agentic flows
Arindam Mitra, Luciano Del Corro, Guoqing Zheng, Shweti Mahajan, Dany Rouhana, Andres Codas, Yadong Lu, Wei-ge Chen, Olga Vrousgos, Corby Rosset, et al. 2024 · 2024
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Breaking down the metrics: A comparative analysis of llm benchmarks
Valentina Porcu and Aneta Havlínová. 2024 · 2024
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Mag-v: A multi-agent framework for synthetic data generation and verification
Saptarshi Sengupta, Kristal Curtis, Akshay Mallipeddi, Abhinav Mathur, Joseph Ross, and Liang Gou. 2024 · 2024
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Synthesizing post-training data for llms through multi-agent simulation
Shuo Tang, Xianghe Pang, Zexi Liu, Bohan Tang, Rui Ye, Xiaowen Dong, Yanfeng Wang, and Siheng Chen. 2024 · 2024
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Yun He, Di Jin, Chaoqi Wang, Chloe Bi, Karishma Mandyam, Hejia Zhang, Chen Zhu, Ning Li, Tengyu Xu, Hongjiang Lv, et al. 2024 · 2024
Cited alongside, same era.
Aaron Hurst, Adam Lerer, Adam P Goucher, Adam Perelman, Aditya Ramesh, Aidan Clark, AJ Ostrow, Akila Welihinda, Alan Hayes, Alec Radford, et al. 2024 · 2024
Cited alongside, same era.
Aaron Jaech, Adam Kalai, Adam Lerer, Adam Richardson, Ahmed El-Kishky, Aiden Low, Alec Helyar, Aleksander Madry, Alex Beutel, Alex Carney, et al. 2024 · 2024
Cited alongside, same era.
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. 2024 · 2024
Cited alongside, same era.
Mt-eval: A multi-turn capabilities evaluation benchmark for large language models
Wai-Chung Kwan, Xingshan Zeng, Yuxin Jiang, Yufei Wang, Liangyou Li, Lifeng Shang, Xin Jiang, Qun Liu, and Kam-Fai Wong. 2024 · 2024
Cited alongside, same era.
Seed-bench-2-plus: Benchmarking multimodal large language models with text-rich visual comprehension
Bohao Li, Yuying Ge, Yi Chen, Yixiao Ge, Ruimao Zhang, and Ying Shan. 2024 · 2024
Cited alongside, same era.
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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 · 2024
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An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, et al. 2024 · 2024
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τ \tau -bench: A benchmark for tool-agent-user interaction in real-world domains
Shunyu Yao, Noah Shinn, Pedram Razavi, and Karthik Narasimhan. 2024 · 2024
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A careful examination of large language model performance on grade school arithmetic
Hugh Zhang, Jeff Da, Dean Lee, Vaughn Robinson, Catherine Wu, Will Song, Tiffany Zhao, Pranav Raja, Dylan Slack, Qin Lyu, et al. 2024 · 2024
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Mmbench: Is your multi-modal model an all-around player?
Yuan Liu, Haodong Duan, Yuanhan Zhang, Bo Li, Songyang Zhang, Wangbo Zhao, Yike Yuan, Jiaqi Wang, Conghui He, Ziwei Liu, et al. 2025 · 2025
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