Learning to Refine with Fine-Grained Natural Language Feedback

RoBERTa: A Robustly Optimized BERT Pretraining Approach

Original

Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907

Earlier work this paper cites.

Binary codes capable of correcting deletions, insertions, and reversals

Vladimir I Levenshtein et al. 1966 · 1966

Earlier work this paper cites.

Can a suit of armor conduct electricity? a new dataset for open book question answering

Todor Mihaylov, Peter Clark, Tushar Khot, and Ashish Sabharwal. 2018 · 2018

Earlier work this paper cites.

Inherent disagreements in human textual inferences

Ellie Pavlick and Tom Kwiatkowski. 2019 · 2019

Earlier work this paper cites.

Uncertain natural language inference

Tongfei Chen, Zhengping Jiang, Adam Poliak, Keisuke Sakaguchi, and Benjamin Van Durme. 2020 · 2020

Earlier work this paper cites.

TRL: Transformer Reinforcement Learning

Leandro von Werra, Younes Belkada, Lewis Tunstall, Edward Beeching, Tristan Thrush, Nathan Lambert, and Shengyi Huang. 2020 · 2020

Earlier work this paper cites.

What can we learn from collective human opinions on natural language inference data?

Yixin Nie, Xiang Zhou, and Mohit Bansal. 2020 · 2020

Earlier work this paper cites.

Training verifiers to solve math word problems

Original

Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman. 2021 · 2021

Earlier work this paper cites.

Investigating memorization of conspiracy theories in text generation

Sharon Levy, Michael Saxon, and William Yang Wang. 2021 · 2021

Earlier work this paper cites.

TruthfulQA: Measuring How Models Mimic Human Falsehoods

Stephanie C. Lin, Jacob Hilton, and Owain Evans. 2021 · 2021

Earlier work this paper cites.

Copy that! editing sequences by copying spans

Sheena Panthaplackel, Miltiadis Allamanis, and Marc Brockschmidt. 2021 · 2021

Earlier work this paper cites.

Evidence-based factual error correction

James Thorne and Andreas Vlachos. 2021 · 2021

Earlier work this paper cites.

MediaSum: A large-scale media interview dataset for dialogue summarization

Chenguang Zhu, Yang Liu, Jie Mei, and Michael Zeng. 2021 · 2021

Earlier work this paper cites.

Correcting diverse factual errors in abstractive summarization via post-editing and language model infilling

Vidhisha Balachandran, Hannaneh Hajishirzi, William Cohen, and Yulia Tsvetkov. 2022 · 2022

Earlier work this paper cites.

CodeT: Code Generation with Generated Tests

Original

Bei Chen, Fengji Zhang, Anh Nguyen, Daoguang Zan, Zeqi Lin, Jian-Guang Lou, and Weizhu Chen. 2022 · 2022

Earlier work this paper cites.

Improving factual consistency in summarization with compression-based post-editing

Alex Fabbri, Prafulla Kumar Choubey, Jesse Vig, Chien-Sheng Wu, and Caiming Xiong. 2022 · 2022

Earlier work this paper cites.

LoRA: Low-rank adaptation of large language models

Edward J Hu, yelong shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2022 · 2022

Earlier work this paper cites.

Self-critiquing models for assisting human evaluators

Original

William Saunders, Catherine Yeh, Jeff Wu, Steven Bills, Long Ouyang, Jonathan Ward, and Jan Leike. 2022 · 2022

Earlier work this paper cites.

The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning

Xi Ye and Greg Durrett. 2022 · 2022

Earlier work this paper cites.

RL4F: Generating natural language feedback with reinforcement learning for repairing model outputs

Afra Feyza Akyurek, Ekin Akyurek, Ashwin Kalyan, Peter Clark, Derry Tanti Wijaya, and Niket Tandon. 2023 · 2023

Earlier work this paper cites.

UltraFeedback: Boosting Language Models with High-quality Feedback

Original

Ganqu Cui, Lifan Yuan, Ning Ding, Guanming Yao, Wei Zhu, Yuan Ni, Guotong Xie, Zhiyuan Liu, and Maosong Sun. 2023 · 2023

Earlier work this paper cites.

Enhancing chat language models by scaling high-quality instructional conversations

Ning Ding, Yulin Chen, Bokai Xu, Yujia Qin, Shengding Hu, Zhiyuan Liu, Maosong Sun, and Bowen Zhou. 2023 · 2023

Cited alongside, same era.

FLEEK: Factual error detection and correction with evidence retrieved from external knowledge

Farima Fatahi Bayat, Kun Qian, Benjamin Han, Yisi Sang, Anton Belyy, Samira Khorshidi, Fei Wu, Ihab Ilyas, and Yunyao Li. 2023 · 2023

Cited alongside, same era.

Self-verification improves few-shot clinical information extraction

Zelalem Gero, Chandan Singh, Hao Cheng, Tristan Naumann, Michel Galley, Jianfeng Gao, and Hoifung Poon. 2023 · 2023

Cited alongside, same era.

SelfEvolve: A Code Evolution Framework via Large Language Models

Original

Shuyang Jiang, Yuhao Wang, and Yu Wang. 2023 · 2023

Cited alongside, same era.

Prometheus: Inducing evaluation capability in language models

Seungone Kim, Jamin Shin, Yejin Cho, Joel Jang, Shayne Longpre, Hwaran Lee, Sangdoo Yun, Seongjin Shin, Sungdong Kim, James Thorne, et al. 2023 · 2023

Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference

Original

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

Closest in time.

Alpacafarm: A simulation framework for methods that learn from human feedback

Yann Dubois, Chen Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy S Liang, and Tatsunori B Hashimoto. 2024 · 2024

Closest in time.

CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing

Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen, Yujiu Yang, Nan Duan, and Weizhu Chen. 2024 · 2024

Closest in time.

TIGERScore: Building Explainable Metric for All Text Generation Task

Dongfu Jiang, Yishan Li, Ge Zhang, Wenhao Huang, Bill Yuchen Lin, and Wenhu Chen. 2024 · 2024

Closest in time.

Leveraging Large Language Models for NLG Evaluation: A Survey

Original