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Reward models are essential for aligning large language models (LLMs) with human preferences.
Latent retrieval for weakly supervised open domain question answering
Kenton Lee, Ming-Wei Chang, and Kristina Toutanova. 2019 · 1906
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Fine-tuning language models from human preferences
Daniel M Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B Brown, Alec Radford, Dario Amodei, Paul Christiano, and Geoffrey Irving. 2019 · 1909
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A law of comparative judgment
LL Thurstone. 1927 · 1927
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The probabilistic relevance framework: Bm25 and beyond
Stephen Robertson, Hugo Zaragoza, et al. 2009 · 2009
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Deep reinforcement learning from human preferences
Paul F Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, and Dario Amodei. 2017 · 2017
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Cross-lingual language model pretraining
Alexis Conneau and Guillaume Lample. 2019 · 2019
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick SH Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
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Learning to summarize with human feedback
Nisan Stiennon, Long Ouyang, Jeffrey Wu, Daniel Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F Christiano. 2020 · 2020
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What makes good in-context examples for gpt- 3 3 ?
Jiachang Liu, Dinghan Shen, Yizhe Zhang, Bill Dolan, Lawrence Carin, and Weizhu Chen. 2021 · 2021
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Webgpt: Browser-assisted question-answering with human feedback
Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, et al. 2021 · 2021
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Learning to retrieve prompts for in-context learning
Ohad Rubin, Jonathan Herzig, and Jonathan Berant. 2021 · 2021
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Language models are few-shot multilingual learners
Genta Indra Winata, Andrea Madotto, Zhaojiang Lin, Rosanne Liu, Jason Yosinski, and Pascale Fung. 2021 · 2021
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How Do Multilingual Encoders Learn Cross-Lingual Representation?
Shijie Wu. 2021 · 2021
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Differentiable prompt makes pre-trained language models better few-shot learners
Ningyu Zhang, Luoqiu Li, Xiang Chen, Shumin Deng, Zhen Bi, Chuanqi Tan, Fei Huang, and Huajun Chen. 2021 · 2021
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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 · 2022
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Diverse demonstrations improve in-context compositional generalization
Itay Levy, Ben Bogin, and Jonathan Berant. 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.
Zhiyong Wu, Yaoxiang Wang, Jiacheng Ye, and Lingpeng Kong. 2022 · 2022
Cited alongside, same era.
Active example selection for in-context learning
Yiming Zhang, Shi Feng, and Chenhao Tan. 2022 · 2022
Cited alongside, same era.
Do multilingual language models think better in english?
Julen Etxaniz, Gorka Azkune, Aitor Soroa, Oier Lopez de Lacalle, and Mikel Artetxe. 2023 · 2023
Cited alongside, same era.
Immune: Improving safety against jailbreaks in multi-modal llms via inference-time alignment
Soumya Suvra Ghosal, Souradip Chakraborty, Vaibhav Singh, Tianrui Guan, Mengdi Wang, Ahmad Beirami, Furong Huang, Alvaro Velasquez, Dinesh Manocha, and Amrit Singh Bedi. 2024 · 2024
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M-rewardbench: Evaluating reward models in multilingual settings
Srishti Gureja, Lester James V Miranda, Shayekh Bin Islam, Rishabh Maheshwary, Drishti Sharma, Gusti Winata, Nathan Lambert, Sebastian Ruder, Sara Hooker, and Marzieh Fadaee. 2024 · 2024
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Cross-lingual transfer of reward models in multilingual alignment
Jiwoo Hong, Noah Lee, Rodrigo Martínez-Castaño, César Rodríguez, and James Thorne. 2024 · 2024
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Pku-saferlhf: Towards multi-level safety alignment for llms with human preference
Jiaming Ji, Donghai Hong, Borong Zhang, Boyuan Chen, Josef Dai, Boren Zheng, Tianyi Qiu, Boxun Li, and Yaodong Yang. 2024 · 2024
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alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Haoyang Huang, Tianyi Tang, Dongdong Zhang, Wayne Xin Zhao, Ting Song, Yan Xia, and Furu Wei. 2023 · 2023
Cited alongside, same era.
Unified demonstration retriever for in-context learning
Xiaonan Li, Kai Lv, Hang Yan, Tianyang Lin, Wei Zhu, Yuan Ni, Guotong Xie, Xiaoling Wang, and Xipeng Qiu. 2023 · 2023
Cited alongside, same era.
Finding support examples for in-context learning
Xiaonan Li and Xipeng Qiu. 2023 · 2023
Cited alongside, same era.
Dr. icl: Demonstration-retrieved in-context learning
Man Luo, Xin Xu, Zhuyun Dai, Panupong Pasupat, Mehran Kazemi, Chitta Baral, Vaiva Imbrasaite, and Vincent Y Zhao. 2023 · 2023
Cited alongside, same era.
In-context example selection with influences
Tai Nguyen and Eric Wong. 2023 · 2023
Cited alongside, same era.
In-context learning with iterative demonstration selection
Chengwei Qin, Aston Zhang, Anirudh Dagar, and Wenming Ye. 2023 · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Reticl: Sequential retrieval of in-context examples with reinforcement learning
Alexander Scarlatos and Andrew Lan. 2023 · 2023
Cited alongside, same era.
Maxim Khanov, Jirayu Burapacheep, and Yixuan Li. 2024 · 2024
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Rewardbench: Evaluating reward models for language modeling
Nathan Lambert, Valentina Pyatkin, Jacob Morrison, LJ Miranda, Bill Yuchen Lin, Khyathi Chandu, Nouha Dziri, Sachin Kumar, Tom Zick, Yejin Choi, Noah A. Smith, and Hannaneh Hajishirzi. 2024 · 2024
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Xampler: Learning to retrieve cross-lingual in-context examples
Peiqin Lin, André FT Martins, and Hinrich Schütze. 2024 · 2024
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Skywork-reward: Bag of tricks for reward modeling in llms
Chris Yuhao Liu, Liang Zeng, Jiacai Liu, Rui Yan, Jujie He, Chaojie Wang, Shuicheng Yan, Yang Liu, and Yahui Zhou. 2024 · 2024
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Controlled decoding from language models
Sidharth Mudgal, Jong Lee, Harish Ganapathy, YaGuang Li, Tao Wang, Yanping Huang, Zhifeng Chen, Heng-Tze Cheng, Michael Collins, Trevor Strohman, Jilin Chen, Alex Beutel, and Ahmad Beirami. 2024 · 2024
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Mapo: Advancing multilingual reasoning through multilingual alignment-as-preference optimization
Shuaijie She, Wei Zou, Shujian Huang, Wenhao Zhu, Xiang Liu, Xiang Geng, and Jiajun Chen. 2024 · 2024
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Harman Singh, Nitish Gupta, Shikhar Bharadwaj, Dinesh Tewari, and Partha Talukdar. 2024 · 2024
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Reuse your rewards: Reward model transfer for zero-shot cross-lingual alignment
Zhaofeng Wu, Ananth Balashankar, Yoon Kim, Jacob Eisenstein, and Ahmad Beirami. 2024 · 2024
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Regularizing hidden states enables learning generalizable reward model for llms
Rui Yang, Ruomeng Ding, Yong Lin, Huan Zhang, and Tong Zhang. 2024 · 2024
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Tianyang Zhong, Zhenyuan Yang, Zhengliang Liu, Ruidong Zhang, Yiheng Liu, Haiyang Sun, Yi Pan, Yiwei Li, Yifan Zhou, Hanqi Jiang, et al. 2024 · 2024
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PromptRefine: Enhancing few-shot performance on low-resource Indic languages with example selection from related example banks
Soumya Suvra Ghosal, Soumyabrata Pal, Koyel Mukherjee, and Dinesh Manocha. 2025 · 2025
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The multilingual mind: A survey of multilingual reasoning in language models
Akash Ghosh, Debayan Datta, Sriparna Saha, and Chirag Agarwal. 2025 · 2025
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