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It is imperative for Large language models (LLMs) to follow instructions with elaborate requirements (i.e.
Language models are few-shot learners
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Think you have solved question answering? try arc, the ai2 reasoning challenge
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Language models are unsupervised multitask learners
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Glm: General language model pretraining with autoregressive blank infilling
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Lora: Low-rank adaptation of large language models
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Truthfulqa: Measuring how models mimic human falsehoods
Stephanie Lin, Jacob Hilton, and Owain Evans. 2021 · 2021
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Controllable text generation with language constraints
Howard Chen, Huihan Li, Danqi Chen, and Karthik Narasimhan. 2022 · 2022
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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
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Cesar: Automatic induction of compositional instructions for multi-turn dialogs
Taha Aksu, Devamanyu Hazarika, Shikib Mehri, Seokhwan Kim, Dilek Hakkani-Tur, Yang Liu, and Mahdi Namazifar. 2023 · 2023
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Rohan Anil, Andrew M Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, et al. 2023 · 2023
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A comprehensive evaluation of constrained text generation for large language models
Xiang Chen and Xiaojun Wan. 2023 · 2023
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Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E Gonzalez, et al. 2023 · 2023
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Specializing smaller language models towards multi-step reasoning
Yao Fu, Hao Peng, Litu Ou, Ashish Sabharwal, and Tushar Khot. 2023 · 2023
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Koala: A dialogue model for academic research
Xinyang Geng, Arnav Gudibande, Hao Liu, Eric Wallace, Pieter Abbeel, Sergey Levine, and Dawn Song. 2023 · 2023
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Contrastive prefence learning: Learning from human feedback without rl
Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn, Scott Niekum, W Bradley Knox, and Dorsa Sadigh. 2023 · 2023
Collie: Systematic construction of constrained text generation tasks
Shunyu Yao, Howard Chen, Austin W Hanjie, Runzhe Yang, and Karthik Narasimhan. 2023 · 2023
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Llm-driven instruction following: Progresses and concerns
Wenpeng Yin, Qinyuan Ye, Pengfei Liu, Xiang Ren, and Hinrich Schütze. 2023 · 2023
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Tell your model where to attend: Post-hoc attention steering for llms
Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, and Tuo Zhao. 2023 · 2023
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Benchmarking large language models on controllable generation under diversified instructions
Yihan Chen, Benfeng Xu, Quan Wang, Yi Liu, and Zhendong Mao. 2024 · 2024
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Can large language models understand real-world complex instructions?
Qianyu He, Jie Zeng, Wenhao Huang, Lina Chen, Jin Xiao, Qianxi He, Xunzhe Zhou, Jiaqing Liang, and Yanghua Xiao. 2024 · 2024
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Orca 2: Teaching small language models how to reason
Arindam Mitra, Luciano Del Corro, Shweti Mahajan, Andres Codas, Clarisse Simoes, Sahaj Agarwal, Xuxi Chen, Anastasia Razdaibiedina, Erik Jones, Kriti Aggarwal, et al. 2023 · 2023
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Norman Mu, Sarah Chen, Zifan Wang, Sizhe Chen, David Karamardian, Lulwa Aljeraisy, Dan Hendrycks, and David Wagner. 2023 · 2023
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Orca: Progressive learning from complex explanation traces of gpt-4
Subhabrata Mukherjee, Arindam Mitra, Ganesh Jawahar, Sahaj Agarwal, Hamid Palangi, and Ahmed Awadallah. 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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Evaluating large language models on controlled generation tasks
Jiao Sun, Yufei Tian, Wangchunshu Zhou, Nan Xu, Qian Hu, Rahul Gupta, John Wieting, Nanyun Peng, and Xuezhe Ma. 2023 · 2023
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Alpaca: A strong, replicable instruction-following model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B Hashimoto. 2023 · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
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Openassistant conversations-democratizing large language model alignment
Andreas Köpf, Yannic Kilcher, Dimitri von Rütte, Sotiris Anagnostidis, Zhi Rui Tam, Keith Stevens, Abdullah Barhoum, Duc Nguyen, Oliver Stanley, Richárd Nagyfi, et al. 2024 · 2024
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A comprehensive survey on instruction following
Renze Lou, Kai Zhang, and Wenpeng Yin. 2024 · 2024
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Infobench: Evaluating instruction following ability in large language models
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Conifer: Improving complex constrained instruction-following ability of large language models
Haoran Sun, Lixin Liu, Junjie Li, Fengyu Wang, Baohua Dong, Ran Lin, and Ruohui Huang. 2024 · 2024
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From instructions to constraints: Language model alignment with automatic constraint verification
Fei Wang, Chao Shang, Sarthak Jain, Shuai Wang, Qiang Ning, Bonan Min, Vittorio Castelli, Yassine Benajiba, and Dan Roth. 2024 · 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 · 2024
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Haoran Xu, Amr Sharaf, Yunmo Chen, Weiting Tan, Lingfeng Shen, Benjamin Van Durme, Kenton Murray, and Young Jin Kim. 2024 · 2024
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Contrastive instruction tuning
Tianyi Yan, Fei Wang, James Y Huang, Wenxuan Zhou, Fan Yin, Aram Galstyan, Wenpeng Yin, and Muhao Chen. 2024 · 2024
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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 Xing, et al. 2024 · 2024
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Lima: Less is more for alignment
Chunting Zhou, Pengfei Liu, Puxin Xu, Srinivasan Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, et al. 2024 · 2024
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