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Large Language Models (LLMs) are nowadays expected to generate content aligned with human preferences.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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An efficient a* search algorithm for statistical machine translation
Franz Josef Och, Nicola Ueffing, and Hermann Ney. 2001 · 2001
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Approximate factoring for a* search
Aria Haghighi, John DeNero, and Dan Klein. 2007 · 2007
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Cube pruning as heuristic search
Mark Hopkins and Greg Langmead. 2009 · 2009
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A diversity-promoting objective function for neural conversation models
Jiwei Li, Michel Galley, Chris Brockett, Jianfeng Gao, and Bill Dolan. 2016a · 2016
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Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2018 · 2018
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Don’t give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization
Shashi Narayan, Shay B. Cohen, and Mirella Lapata. 2018 · 2018
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Improving beam search by removing monotonic constraint for neural machine translation
Raphael Shu and Hideki Nakayama. 2018 · 2018
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A general-purpose algorithm for constrained sequential inference
Daniel Deutsch, Shyam Upadhyay, and Dan Roth. 2019 · 2019
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The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2019 · 2019
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Importance of search and evaluation strategies in neural dialogue modeling
Ilia Kulikov, Alexander Miller, Kyunghyun Cho, and Jason Weston. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
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Natural language generation with keyword constraints– a hybrid approach using supervised and reinforcement learning
Sailik Sengupta, He He, Batool Haider, Spandana Gella, and Mona Diab. 2019 · 2019
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CommonGen: A constrained text generation challenge for generative commonsense reasoning
Bill Yuchen Lin, Wangchunshu Zhou, Ming Shen, Pei Zhou, Chandra Bhagavatula, Yejin Choi, and Xiang Ren. 2020 · 2020
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Best-first beam search
Clara Meister, Tim Vieira, and Ryan Cotterell. 2020 · 2020
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SummEval: Re-evaluating summarization evaluation
Alexander R. Fabbri, Wojciech Kryściński, Bryan McCann, Caiming Xiong, Richard Socher, and Dragomir Radev. 2021 · 2021
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GeDi: Generative discriminator guided sequence generation
Ben Krause, Akhilesh Deepak Gotmare, Bryan McCann, Nitish Shirish Keskar, Shafiq Joty, Richard Socher, and Nazneen Fatema Rajani. 2021 · 2021
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NeuroLogic decoding: (un)supervised neural text generation with predicate logic constraints
Ximing Lu, Peter West, Rowan Zellers, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2021 · 2021
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Towards grounded natural language proof generation
Sean Welleck, Jiacheng Liu, Jesse Michael Han, and Yejin Choi. 2021 · 2021
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FUDGE: Controlled text generation with future discriminators
Kevin Yang and Dan Klein. 2021 · 2021
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NeuroLogic a*esque decoding: Constrained text generation with lookahead heuristics
Ximing Lu, Sean Welleck, Peter West, Liwei Jiang, Jungo Kasai, Daniel Khashabi, Ronan Le Bras, Lianhui Qin, Youngjae Yu, Rowan Zellers, Noah A. Smith, and Yejin Choi. 2022 · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
Cited alongside, same era.
Cold decoding: Energy-based constrained text generation with langevin dynamics
Lianhui Qin, Sean Welleck, Daniel Khashabi, and Yejin Choi. 2022 · 2022
Cited alongside, same era.
G-eval: Nlg evaluation using gpt-4 with better human alignment, may 2023
Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu. 2023 · 2023
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Guilherme Penedo, Quentin Malartic, Daniel Hesslow, Ruxandra Cojocaru, Alessandro Cappelli, Hamza Alobeidli, Baptiste Pannier, Ebtesam Almazrouei, and Julien Launay. 2023 · 2023
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Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Stefano Ermon, Christopher D Manning, and Chelsea Finn. 2023 · 2023
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On second thought, let’s not think step by step! bias and toxicity in zero-shot reasoning
Omar Shaikh, Hongxin Zhang, William Held, Michael Bernstein, and Diyi Yang. 2023 · 2023
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al. 2022 · 2022
Cited alongside, same era.
Opt: Open pre-trained transformer language models
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al. 2022 · 2022
Cited alongside, same era.
It’s mbr all the way down: Modern generation techniques through the lens of minimum bayes risk
Amanda Bertsch, Alex Xie, Graham Neubig, and Matthew R Gormley. 2023 · 2023
Cited alongside, same era.
Free dolly: Introducing the world’s first truly open instruction-tuned llm
Mike Conover, Matt Hayes, Ankit Mathur, Jianwei Xie, Jun Wan, Sam Shah, Ali Ghodsi, Patrick Wendell, Matei Zaharia, and Reynold Xin. 2023 · 2023
Cited alongside, same era.
Reward-augmented decoding: Efficient controlled text generation with a unidirectional reward model
Haikang Deng and Colin Raffel. 2023 · 2023
Cited alongside, same era.
Raft: Reward ranked finetuning for generative foundation model alignment
Hanze Dong, Wei Xiong, Deepanshu Goyal, Rui Pan, Shizhe Diao, Jipeng Zhang, Kashun Shum, and Tong Zhang. 2023 · 2023
Cited alongside, same era.
Towards measuring the representation of subjective global opinions in language models
Esin Durmus, Karina Nyugen, Thomas I Liao, Nicholas Schiefer, Amanda Askell, Anton Bakhtin, Carol Chen, Zac Hatfield-Dodds, Danny Hernandez, Nicholas Joseph, et al. 2023 · 2023
Cited alongside, same era.
Feifan Song, Bowen Yu, Minghao Li, Haiyang Yu, Fei Huang, Yongbin Li, and Houfeng Wang. 2023 · 2023
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Introducing mpt-7b: A new standard for open-source, commercially usable llms
MosaicML NLP Team. 2023 · 2023
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Jailbroken: How does llm safety training fail?
Alexander Wei, Nika Haghtalab, and Jacob Steinhardt. 2023 · 2023
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Efficient guided generation for large language models
Brandon T Willard and Rémi Louf. 2023 · 2023
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BREAK: Breaking the dialogue state tracking barrier with beam search and re-ranking
Seungpil Won, Heeyoung Kwak, Joongbo Shin, Janghoon Han, and Kyomin Jung. 2023 · 2023
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Rrhf: Rank responses to align language models with human feedback without tears
Zheng Yuan, Hongyi Yuan, Chuanqi Tan, Wei Wang, Songfang Huang, and Fei Huang. 2023 · 2023
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Benchmarking large language models for news summarization
Tianyi Zhang, Faisal Ladhak, Esin Durmus, Percy Liang, Kathleen McKeown, and Tatsunori B Hashimoto. 2023 · 2023
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Universal and transferable adversarial attacks on aligned language models
Andy Zou, Zifan Wang, J Zico Kolter, and Matt Fredrikson. 2023 · 2023
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Albert Q Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, et al. 2024 · 2024
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ARGS: Alignment as reward-guided search
Maxim Khanov, Jirayu Burapacheep, and Yixuan Li. 2024 · 2024
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RAIN: Your language models can align themselves without finetuning
Yuhui Li, Fangyun Wei, Jinjing Zhao, Chao Zhang, and Hongyang Zhang. 2024 · 2024
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Flap: Flow adhering planning with constrained decoding in llms
Shamik Roy, Sailik Sengupta, Daniele Bonadiman, Saab Mansour, and Arshit Gupta. 2024 · 2024
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Self-evaluation guided beam search for reasoning
Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, James Xu Zhao, Min-Yen Kan, Junxian He, and Michael Xie. 2024 · 2024
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