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Evaluation insights are limited by the availability of high-quality benchmarks.
Phyre: A new benchmark for physical reasoning
Anton Bakhtin, Laurens van der Maaten, Justin Johnson, Laura Gustafson, and Ross Girshick. 2019 · 1908
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Clevr: A diagnostic dataset for compositional language and elementary visual reasoning
Justin Johnson, Bharath Hariharan, Laurens van der Maaten, Li Fei-Fei, C. Lawrence Zitnick, and Ross B. Girshick. 2016 · 1997
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Craft: A benchmark for causal reasoning about forces and interactions
Tayfun Ates, M. Samil Atesoglu, Cagatay Yigit, Ilker Kesen, Mert Kobas, Erkut Erdem, Aykut Erdem, Tilbe Goksun, and Deniz Yuret. 2020 · 2012
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Vqa: Visual question answering
Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C. Lawrence Zitnick, and Devi Parikh. 2015 · 2015
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Clevrer: Collision events for video representation and reasoning
Kexin Yi, Chuang Gan, Yunzhu Li, Pushmeet Kohli, Jiajun Wu, Antonio Torralba, and Joshua B. Tenenbaum. 2020 · 2020
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Collie: Systematic construction of constrained text generation tasks
Shunyu Yao, Howard Chen, Austin W. Hanjie, Runzhe Yang, and Karthik Narasimhan. 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
Earlier work this paper cites.
Kitab: Evaluating llms on constraint satisfaction for information retrieval
Marah I Abdin, Suriya Gunasekar, Varun Chandrasekaran, Jerry Li, Mert Yuksekgonul, Rahee Ghosh Peshawaria, Ranjita Naik, and Besmira Nushi. 2024 · 2024
Earlier work this paper cites.
Claude 3.5 sonnet
Anthropic. 2024 · 2024
Earlier work this paper cites.
Assessing and verifying task utility in llm-powered applications
Negar Arabzadeh, Siqing Huo, Nikhil Mehta, Qinqyun Wu, Chi Wang, Ahmed Awadallah, Charles L. A. Clarke, and Julia Kiseleva. 2024 · 2024
Cited alongside, same era.
Eureka: Evaluating and understanding large foundation models
Vidhisha Balachandran, Jingya Chen, Neel Joshi, Besmira Nushi, Hamid Palangi, Eduardo Salinas, Vibhav Vineet, James Woffinden-Luey, and Safoora Yousefi. 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, and 1 others. 2024 · 2024
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Autobencher: Creating salient, novel, difficult datasets for language models
Xiang Lisa Li, Evan Zheran Liu, Percy Liang, and Tatsunori Hashimoto. 2024 · 2024
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Benchmark self-evolving: A multi-agent framework for dynamic llm evaluation
Siyuan Wang, Zhuohan Long, Zhihao Fan, Zhongyu Wei, and Xuanjing Huang. 2024 · 2024
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Xiaohan Yuan, Jinfeng Li, Dongxia Wang, Yuefeng Chen, Xiaofeng Mao, Longtao Huang, Hui Xue, Wenhai Wang, Kui Ren, and Jingyi Wang. 2024 · 2024
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Attention satisfies: A constraint-satisfaction lens on factual errors of language models
Mert Yuksekgonul, Varun Chandrasekaran, Erik Jones, Suriya Gunasekar, Ranjita Naik, Hamid Palangi, Ece Kamar, and Besmira Nushi. 2024 · 2024
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Natural plan: Benchmarking llms on natural language planning
Huaixiu Steven Zheng, Swaroop Mishra, Hugh Zhang, Xinyun Chen, Minmin Chen, Azade Nova, Le Hou, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, and Denny Zhou. 2024 · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
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Chunqiu Steven Xia, Yinlin Deng, and Lingming Zhang. 2024a
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Fofo: A benchmark to evaluate llms’ format-following capability
Congying Xia, Chen Xing, Jiangshu Du, Xinyi Yang, Yihao Feng, Ran Xu, Wenpeng Yin, and Caiming Xiong. 2024b
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Language model developers should report train-test overlap
Andy K Zhang, Kevin Klyman, Yifan Mai, Yoav Levine, Yian Zhang, Rishi Bommasani, and Percy Liang. 2024a
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Dyval: Dynamic evaluation of large language models for reasoning tasks
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
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