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Instruction-following is essential for aligning large language models (LLMs) with user intent.
Minerva: Accelerating data analysis in next-generation ssds
Arup De, Maya Gokhale, Rajesh Gupta, and Steven Swanson · 2013
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Measuring mathematical problem solving with the math dataset
Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt · 2021
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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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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
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Aime problem set 1983-2024, 2023
Hemish Veeraboina · 2023
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Instruction-following evaluation for large language models
Jeffrey Zhou, Tianjian Lu, Swaroop Mishra, Siddhartha Brahma, Sujoy Basu, Yi Luan, Denny Zhou, and Le Hou · 2023
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Followbench: A multi-level fine-grained constraints following benchmark for large language models
Yuxin Jiang, Yufei Wang, Xingshan Zeng, Wanjun Zhong, Liangyou Li, Fei Mi, Lifeng Shang, Xin Jiang, Qun Liu, and Wei Wang · 2023
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Alpacafarm: A simulation framework for methods that learn from human feedback, 2023
Yann Dubois, Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto · 2023
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Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality, March 2023
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing · 2023
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Efficient memory management for large language model serving with pagedattention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, and Ion Stoica · 2023
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Olympiadbench: A challenging benchmark for promoting agi with olympiad-level bilingual multimodal scientific problems, 2024
Chaoqun He, Renjie Luo, Yuzhuo Bai, Shengding Hu, Zhen Leng Thai, Junhao Shen, Jinyi Hu, Xu Han, Yujie Huang, Yuxiang Zhang, Jie Liu, Lei Qi, Zhiyuan Liu, and Maosong Sun · 2024
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FOFO: A benchmark to evaluate LLMs’ format-following capability
Congying Xia, Chen Xing, Jiangshu Du, Xinyi Yang, Yihao Feng, Ran Xu, Wenpeng Yin, and Caiming Xiong · 2024
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Struc-bench: Are large language models good at generating complex structured tabular data?
Xiangru Tang, Yiming Zong, Jason Phang, Yilun Zhao, Wangchunshu Zhou, Arman Cohan, and Mark Gerstein · 2024
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Multi-if: Benchmarking llms on multi-turn and multilingual instructions following
Yun He, Di Jin, Chaoqi Wang, Chloe Bi, Karishma Mandyam, Hejia Zhang, Chen Zhu, Ning Li, Tengyu Xu, Hongjiang Lv, et al · 2024
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Xiaodong Wu, Minhao Wang, Yichen Liu, Xiaoming Shi, He Yan, Xiangju Lu, Junmin Zhu, and Wei Zhang · 2024
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RefuteBench: Evaluating refuting instruction-following for large language models
Jianhao Yan, Yun Luo, and Yue Zhang · 2024
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Benchmarking complex instruction-following with multiple constraints composition
Bosi Wen, Pei Ke, Xiaotao Gu, Lindong Wu, Hao Huang, Jinfeng Zhou, Wenchuang Li, Binxin Hu, Wendy Gao, Jiaxing Xu, et al · 2024
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Aaron Hurst, Adam Lerer, Adam P Goucher, Adam Perelman, Aditya Ramesh, Aidan Clark, AJ Ostrow, Akila Welihinda, Alan Hayes, Alec Radford, et al · 2024
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Qwen2.5-math technical report: Toward mathematical expert model via self-improvement
An Yang, Beichen Zhang, Binyuan Hui, Bofei Gao, Bowen Yu, Chengpeng Li, Dayiheng Liu, Jianhong Tu, Jingren Zhou, Junyang Lin, Keming Lu, Mingfeng Xue, Runji Lin, Tianyu Liu, Xingzhang Ren, and Zhenru Zhang · 2024
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Roformer: Enhanced transformer with rotary position embedding
Jianlin Su, Murtadha Ahmed, Yu Lu, Shengfeng Pan, Wen Bo, and Yunfeng Liu · 2024
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Deepseekmath: Pushing the limits of mathematical reasoning in open language models
Zhihong Shao, Peiyi Wang, Qihao Zhu, Runxin Xu, Junxiao Song, Xiao Bi, Haowei Zhang, Mingchuan Zhang, YK Li, Y Wu, et al · 2024
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Learning to reason under off-policy guidance, 2025
Jianhao Yan, Yafu Li, Zican Hu, Zhi Wang, Ganqu Cui, Xiaoye Qu, Yu Cheng, and Yue Zhang · 2025
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Thinking preference optimization
Wang Yang, Hongye Jin, Jingfeng Yang, Vipin Chaudhary, and Xiaotian Han · 2025
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Structflowbench: A structured flow benchmark for multi-turn instruction following
Jinnan Li, Jinzhe Li, Yue Wang, Yi Chang, and Yuan Wu · 2025
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Can language models follow multiple turns of entangled instructions?
Chi Han · 2025
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Ved Sirdeshmukh, Kaustubh Deshpande, Johannes Mols, Lifeng Jin, Ed-Yeremai Cardona, Dean Lee, Jeremy Kritz, Willow Primack, Summer Yue, and Chen Xing · 2025
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Mingyu Jin, Qinkai Yu, Dong Shu, Haiyan Zhao, Wenyue Hua, Yanda Meng, Yongfeng Zhang, and Mengnan Du · 2024
Cited alongside, same era.
A survey of efficient reasoning for large reasoning models: Language, multimodality, and beyond
Xiaoye Qu, Yafu Li, Zhaochen Su, Weigao Sun, Jianhao Yan, Dongrui Liu, Ganqu Cui, Daizong Liu, Shuxian Liang, Junxian He, et al · 2025
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning, 2025
DeepSeek-AI · 2025
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Deepseek-prover-v2: Advancing formal mathematical reasoning via reinforcement learning for subgoal decomposition, 2025
Z. Z. Ren, Zhihong Shao, Junxiao Song, Huajian Xin, Haocheng Wang, Wanjia Zhao, Liyue Zhang, Zhe Fu, Qihao Zhu, Dejian Yang, Z. F. Wu, Zhibin Gou, Shirong Ma, Hongxuan Tang, Yuxuan Liu, Wenjun Gao, Daya Guo, and Chong Ruan · 2025
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Crossing the reward bridge: Expanding rl with verifiable rewards across diverse domains, 2025
Yi Su, Dian Yu, Linfeng Song, Juntao Li, Haitao Mi, Zhaopeng Tu, Min Zhang, and Dong Yu · 2025
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A survey on llm-as-a-judge, 2025
Jiawei Gu, Xuhui Jiang, Zhichao Shi, Hexiang Tan, Xuehao Zhai, Chengjin Xu, Wei Li, Yinghan Shen, Shengjie Ma, Honghao Liu, Saizhuo Wang, Kun Zhang, Yuanzhuo Wang, Wen Gao, Lionel Ni, and Jian Guo · 2025
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Niklas Muennighoff, Zitong Yang, Weijia Shi, Xiang Lisa Li, Li Fei-Fei, Hannaneh Hajishirzi, Luke Zettlemoyer, Percy Liang, Emmanuel Candès, and Tatsunori Hashimoto · 2025
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Limo: Less is more for reasoning, 2025
Yixin Ye, Zhen Huang, Yang Xiao, Ethan Chern, Shijie Xia, and Pengfei Liu · 2025
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Xifbench: Evaluating large language models on multilingual instruction following
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IHEval: Evaluating language models on following the instruction hierarchy
Zhihan Zhang, Shiyang Li, Zixuan Zhang, Xin Liu, Haoming Jiang, Xianfeng Tang, Yifan Gao, Zheng Li, Haodong Wang, Zhaoxuan Tan, Yichuan Li, Qingyu Yin, Bing Yin, and Meng Jiang · 2025
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Chain-of-instructions: Compositional instruction tuning on large language models
Shirley Anugrah Hayati, Taehee Jung, Tristan Bodding-Long, Sudipta Kar, Abhinav Sethy, Joo-Kyung Kim, and Dongyeop Kang · 2025
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Refutebench 2.0 – agentic benchmark for dynamic evaluation of llm responses to refutation instruction, 2025
Jianhao Yan, Yun Luo, and Yue Zhang · 2025
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Qwen3, April 2025
Qwen Team · 2025
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Simplerl-zoo: Investigating and taming zero reinforcement learning for open base models in the wild
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Deepscaler: Surpassing o1-preview with a 1.5b model by scaling rl, 2025
Michael Luo, Sijun Tan, Justin Wong, Xiaoxiang Shi, William Y. Tang, Manan Roongta, Colin Cai, Jeffrey Luo, Li Erran Li, Raluca Ada Popa, and Ion Stoica · 2025
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L1: Controlling how long a reasoning model thinks with reinforcement learning
Pranjal Aggarwal and Sean Welleck · 2025
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Open-reasoner-zero: An open source approach to scaling up reinforcement learning on the base model
Jingcheng Hu, Yinmin Zhang, Qi Han, Daxin Jiang, Xiangyu Zhang, and Heung-Yeung Shum · 2025
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Open r1: A fully open reproduction of deepseek-r1, January 2025
Hugging Face · 2025
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Qwq-32b: Embracing the power of reinforcement learning, March 2025
Qwen Team · 2025
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Open-reasoner-zero: An open source approach to scaling up reinforcement learning on the base model, 2025
Jingcheng Hu, Yinmin Zhang, Qi Han, Daxin Jiang, Xiangyu Zhang, and Heung-Yeung Shum · 2025
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