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Reliable evaluation of large language models (LLMs) is impeded by two key challenges: objective metrics often fail to reflect human perception of natural language, and exhaustive human labeling is prohibitively expensive.
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Program synthesis with large language models
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Training verifiers to solve math word problems
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Dynabench: Rethinking benchmarking in NLP
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An in-depth look at Gemini’s language abilities
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Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, et al. 2023 · 2023
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Which prompts make the difference? Data prioritization for efficient human LLM evaluation
Meriem Boubdir, Edward Kim, Beyza Ermis, Marzieh Fadaee, and Sara Hooker. 2023 · 2023
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LLaMA: Open and efficient foundation language models
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Anchor points: Benchmarking models with much fewer examples
Rajan Vivek, Kawin Ethayarajh, Diyi Yang, and Douwe Kiela. 2023 · 2023
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WizardLM: Empowering large language models to follow complex instructions
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Chi-Min Chan, Weize Chen, Yusheng Su, Jianxuan Yu, Wei Xue, Shanghang Zhang, Jie Fu, and Zhiyuan Liu. 2023 · 2023
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Code Alpaca: An instruction-following LLaMA model for code generation
Sahil Chaudhary. 2023 · 2023
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Large knowledge model: Perspectives and challenges
Huajun Chen. 2023 · 2023
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InstructEval: Towards holistic evaluation of instruction-tuned large language models
Yew Ken Chia, Pengfei Hong, Lidong Bing, and Soujanya Poria. 2023 · 2023
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Vicuna: An open-source chatbot impressing GPT-4 with 90%* ChatGPT quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E Gonzalez, et al. 2023 · 2023
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Yann Dubois, Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, and Tatsunori B Hashimoto. 2023 · 2023
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Evaluating large language models: A comprehensive survey
Zishan Guo, Renren Jin, Chuang Liu, Yufei Huang, Dan Shi, Linhao Yu, Yan Liu, Jiaxuan Li, Bojian Xiong, Deyi Xiong, et al. 2023 · 2023
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C-Eval: A multi-level multi-discipline chinese evaluation suite for foundation models
Yuzhen Huang, Yuzhuo Bai, Zhihao Zhu, Junlei Zhang, Jinghan Zhang, Tangjun Su, Junteng Liu, Chuancheng Lv, Yikai Zhang, Jiayi Lei, et al. 2023 · 2023
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AGIEval: A human-centric benchmark for evaluating foundation models
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Label-efficient model selection for text generation
Shir Ashury-Tahan, Ariel Gera, Benjamin Sznajder, Leshem Choshen, Liat Ein-Dor, and Eyal Shnarch. 2024 · 2024
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ChatGPT is a remarkable tool—for experts
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Humans or LLMs as the judge? A study on judgement biases
Guiming Hardy Chen, Shunian Chen, Ziche Liu, Feng Jiang, and Benyou Wang. 2024 · 2024
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Chatbot Arena: An open platform for evaluating LLMs by human preference
Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Hao Zhang, Banghua Zhu, Michael Jordan, Joseph E Gonzalez, et al. 2024 · 2024
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How to evaluate reward models for RLHF
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Prometheus 2: An open source language model specialized in evaluating other language models
Seungone Kim, Juyoung Suk, Shayne Longpre, Bill Y Lin, Jamin Shin, Sean Welleck, Graham Neubig, Moontae Lee, Kyungjae Lee, and Minjoon Seo. 2024 · 2024
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SG-Bench: Evaluating LLM safety generalization across diverse tasks and prompt types
Yutao Mou, Shikun Zhang, and Wei Ye. 2024 · 2024
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JudgeBench: A benchmark for evaluating LLM-based judges
Sijun Tan, Siyuan Zhuang, Kyle Montgomery, William Y Tang, Alejandro Cuadron, Chenguang Wang, Raluca Ada Popa, and Ion Stoica. 2024 · 2024
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Rethinking generative large language model evaluation for semantic comprehension
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LongMemEval: Benchmarking chat assistants on long-term interactive memory
Di Wu, Hongwei Wang, Wenhao Yu, Yuwei Zhang, Kai-Wei Chang, and Dong Yu. 2024 · 2024
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SaMer: A scenario-aware multi-dimensional evaluator for large language models
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J1: Incentivizing thinking in LLM-as-a-judge via reinforcement learning
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