Order Matters: Investigate the Position Bias in Multi-constraint Instruction Following

Visualizing and understanding neural models in nlp

Jiwei Li, Xinlei Chen, Eduard Hovy, and Dan Jurafsky. 2016 · 2016

Earlier work this paper cites.

Kendall tau sequence distance: Extending kendall tau from ranks to sequences

Vincent A Cicirello. 2020 · 2020

Earlier work this paper cites.

Perturbed masking: Parameter-free probing for analyzing and interpreting bert

Z Wu, Y Chen, CM Kao, and FUN Liu. 2020 · 2020

Earlier work this paper cites.

Super-naturalinstructions: Generalization via declarative instructions on 1600+ nlp tasks

Original

Yizhong Wang, Swaroop Mishra, Pegah Alipoormolabashi, Yeganeh Kordi, Amirreza Mirzaei, Anjana Arunkumar, Arjun Ashok, Arut Selvan Dhanasekaran, et al. 2022 · 2022

Earlier work this paper cites.

Gpt-4 technical report

Original

Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023

Earlier work this paper cites.

Qwen technical report

Original

Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, et al. 2023 · 2023

Earlier work this paper cites.

The reversal curse: Llms trained on" a is b" fail to learn" b is a"

Original

Lukas Berglund, Meg Tong, Max Kaufmann, Mikita Balesni, Asa Cooper Stickland, Tomasz Korbak, and Owain Evans. 2023 · 2023

Earlier work this paper cites.

Efficient memory management for large language model serving with pagedattention

Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph Gonzalez, Hao Zhang, and Ion Stoica. 2023 · 2023

Earlier work this paper cites.

Self-alignment with instruction backtranslation

Original

Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Luke Zettlemoyer, Omer Levy, Jason Weston, and Mike Lewis. 2023 · 2023

Earlier work this paper cites.

Concise and organized perception facilitates reasoning in large language models

Junjie Liu, Shaotian Yan, Chen Shen, Liang Xie, Wenxiao Wang, and Jieping Ye. 2023 · 2023

Earlier work this paper cites.

Beyond the imitation game: Quantifying and extrapolating the capabilities of language models

Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Shoeb, Abubakar Abid, Adam Fisch, Adam R Brown, Adam Santoro, Aditya Gupta, Adri Garriga-Alonso, et al. 2023 · 2023

Earlier work this paper cites.

Llama 2: Open foundation and fine-tuned chat models

Original

Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023

Earlier work this paper cites.

Self-instruct: Aligning language models with self-generated instructions

Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A Smith, Daniel Khashabi, and Hannaneh Hajishirzi. 2023 · 2023

Earlier work this paper cites.

From language modeling to instruction following: Understanding the behavior shift in llms after instruction tuning

Original

Xuansheng Wu, Wenlin Yao, Jianshu Chen, Xiaoman Pan, Xiaoyang Wang, Ninghao Liu, and Dong Yu. 2023 · 2023

Cited alongside, same era.

Llm-driven instruction following: Progresses and concerns

Wenpeng Yin, Qinyuan Ye, Pengfei Liu, Xiang Ren, and Hinrich Schütze. 2023 · 2023

Cited alongside, same era.

Evaluating Large Language Models at Evaluating Instruction Following

Original

Zhiyuan Zeng, Jiatong Yu, Tianyu Gao, Yu Meng, Tanya Goyal, and Danqi Chen. 2023 · 2023

Cited alongside, same era.

Judging llm-as-a-judge with mt-bench and chatbot arena

Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P Xing, et al. 2023 · 2023

Cited alongside, same era.

Instruction-following evaluation for large language models

Original

Lost in the middle: How language models use long contexts

Nelson F Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang. 2024 · 2024

Later among the works it cites.

Large language model instruction following: A survey of progresses and challenges

Renze Lou, Kai Zhang, and Wenpeng Yin. 2024 · 2024

Later among the works it cites.

Infobench: Evaluating instruction following ability in large language models

Original

Yiwei Qin, Kaiqiang Song, Yebowen Hu, Wenlin Yao, Sangwoo Cho, Xiaoyang Wang, Xuansheng Wu, Fei Liu, Pengfei Liu, and Dong Yu. 2024 · 2024

Later among the works it cites.

Conifer: Improving complex constrained instruction-following ability of large language models

Original

Haoran Sun, Lixin Liu, Junjie Li, Fengyu Wang, Baohua Dong, Ran Lin, and Ruohui Huang. 2024 · 2024

Later among the works it cites.

Found in the middle: Permutation self-consistency improves listwise ranking in large language models