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Evaluating large language model (LLM) based chat assistants is challenging due to their broad capabilities and the inadequacy of existing benchmarks in measuring human preferences.
Position bias in multiple-choice questions
Niels J Blunch · 1984
Earlier work this paper cites.
Evaluations of self and others: Self-enhancement biases in social judgments
Jonathon D Brown · 1986
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Bleu: a method for automatic evaluation of machine translation
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
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Center-of-inattention: Position biases in decision-making
Priya Raghubir and Ana Valenzuela · 2006
Earlier work this paper cites.
Think you have solved question answering? try arc, the ai2 reasoning challenge
Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, and Oyvind Tafjord · 2018
Earlier work this paper cites.
Position bias estimation for unbiased learning to rank in personal search
Xuanhui Wang, Nadav Golbandi, Michael Bendersky, Donald Metzler, and Marc Najork · 2018
Earlier work this paper cites.
Coqa: A conversational question answering challenge
Siva Reddy, Danqi Chen, and Christopher D Manning · 2019
Earlier work this paper cites.
Hellaswag: Can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi · 2019
Earlier work this paper cites.
Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt · 2020
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Look at the first sentence: Position bias in question answering
Miyoung Ko, Jinhyuk Lee, Hyunjae Kim, Gangwoo Kim, and Jaewoo Kang · 2020
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Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021
Earlier work this paper cites.
Training verifiers to solve math word problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, et al · 2021
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Dynabench: Rethinking benchmarking in nlp
Douwe Kiela, Max Bartolo, Yixin Nie, Divyansh Kaushik, Atticus Geiger, Zhengxuan Wu, Bertie Vidgen, Grusha Prasad, Amanpreet Singh, Pratik Ringshia, et al · 2021
Earlier work this paper cites.
Truthfulqa: Measuring how models mimic human falsehoods
Stephanie Lin, Jacob Hilton, and Owain Evans · 2021
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Winogrande: An adversarial winograd schema challenge at scale
Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi · 2021
Earlier work this paper cites.
Finetuned language models are zero-shot learners
Jason Wei, Maarten Bosma, Vincent Y Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M Dai, and Quoc V Le · 2021
Earlier work this paper cites.
Training a helpful and harmless assistant with reinforcement learning from human feedback
Yuntao Bai, Andy Jones, Kamal Ndousse, Amanda Askell, Anna Chen, Nova DasSarma, Dawn Drain, Stanislav Fort, Deep Ganguli, Tom Henighan, et al · 2022
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Flashattention: Fast and memory-efficient exact attention with io-awareness
Tri Dao, Dan Fu, Stefano Ermon, Atri Rudra, and Christopher Ré · 2022
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Mmdialog: A large-scale multi-turn dialogue dataset towards multi-modal open-domain conversation
Jiazhan Feng, Qingfeng Sun, Can Xu, Pu Zhao, Yaming Yang, Chongyang Tao, Dongyan Zhao, and Qingwei Lin · 2022
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Holistic evaluation of language models
Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, et al · 2022
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Koala: A dialogue model for academic research
Xinyang Geng, Arnav Gudibande, Hao Liu, Eric Wallace, Pieter Abbeel, Sergey Levine, and Dawn Song · 2023
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Chatgpt outperforms crowd-workers for text-annotation tasks
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The false promise of imitating proprietary llms
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Openassistant conversations–democratizing large language model alignment
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Swaroop Mishra, Daniel Khashabi, Chitta Baral, and Hannaneh Hajishirzi · 2022
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Training language models to follow instructions with human feedback
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Chain of thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed Chi, Quoc Le, and Denny Zhou · 2022
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Rohan Anil, Andrew M Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, et al · 2023
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Sparks of artificial general intelligence: Early experiments with gpt-4
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The flan collection: Designing data and methods for effective instruction tuning
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Gpt-4 technical report, 2023
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How far can camels go? exploring the state of instruction tuning on open resources
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Wizardlm: Empowering large language models to follow complex instructions
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SkyPilot: An intercloud broker for sky computing
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Agieval: A human-centric benchmark for evaluating foundation models
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Lima: Less is more for alignment
Chunting Zhou, Pengfei Liu, Puxin Xu, Srini Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, et al · 2023
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