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Large language models (LLMs) have been widely integrated into information retrieval to advance traditional techniques.
Axiomatisations of the average and a further generalisation of monotonic sequences
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Variational reasoning about user preferences for conversational recommendation
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Chain of thought prompting elicits reasoning in large language models
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Reasoning with language model prompting: A survey
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A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions
Lei Huang, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, et al · 2023
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Enhancing retrieval-augmented large language models with iterative retrieval-generation synergy
Zhihong Shao, Yeyun Gong, Yelong Shen, Minlie Huang, Nan Duan, and Weizhu Chen · 2023
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Is ChatGPT good at search? investigating large language models as re-ranking agents
Weiwei Sun, Lingyong Yan, Xinyu Ma, Shuaiqiang Wang, Pengjie Ren, Zhumin Chen, Dawei Yin, and Zhaochun Ren · 2023
Learning to explore and select for coverage-conditioned retrieval-augmented generation
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Corrective retrieval augmented generation
Shi-Qi Yan, Jia-Chen Gu, Yun Zhu, and Zhen-Hua Ling · 2024
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Rankrag: Unifying context ranking with retrieval-augmented generation in llms
Yue Yu, Wei Ping, Zihan Liu, Boxin Wang, Jiaxuan You, Chao Zhang, Mohammad Shoeybi, and Bryan Catanzaro · 2024
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Adelie: Aligning large language models on information extraction
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Recomp: Improving retrieval-augmented lms with compression and selective augmentation
Fangyuan Xu, Weijia Shi, and Eunsol Choi · 2023
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Retrieval-augmented generation for large language models: A survey
Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, and Haofen Wang · 2023
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Making retrieval-augmented language models robust to irrelevant context
Ori Yoran, Tomer Wolfson, Ori Ram, and Jonathan Berant · 2023
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Query rewriting in retrieval-augmented large language models
Xinbei Ma, Yeyun Gong, Pengcheng He, Hai Zhao, and Nan Duan · 2023
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Variational reasoning over incomplete knowledge graphs for conversational recommendation
Xiaoyu Zhang, Xin Xin, Dongdong Li, Wenxuan Liu, Pengjie Ren, Zhumin Chen, Jun Ma, and Zhaochun Ren · 2023
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Investigating the factual knowledge boundary of large language models with retrieval augmentation
Ruiyang Ren, Yuhao Wang, Yingqi Qu, Wayne Xin Zhao, Jing Liu, Hao Tian, Hua Wu, Ji-Rong Wen, and Haifeng Wang · 2023
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GPT-4, 2023
OpenAI · 2023
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Weinan Zhang, Junwei Liao, Ning Li, Kounianhua Du, and Jianghao Lin · 2024
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Stochastic rag: End-to-end retrieval-augmented generation through expected utility maximization
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An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, et al · 2024
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Chatqa: Surpassing gpt-4 on conversational qa and rag
Zihan Liu, Wei Ping, Rajarshi Roy, Peng Xu, Chankyu Lee, Mohammad Shoeybi, and Bryan Catanzaro · 2024
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Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn · 2024
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Generate-then-ground in retrieval-augmented generation for multi-hop question answering
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Dspy: Compiling declarative language model calls into state-of-the-art pipelines
O. Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan, Saiful Haq, Ashutosh Sharma, Thomas T. Joshi, Hanna Moazam, et al · 2024
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Atm: Adversarial tuning multi-agent system makes a robust retrieval-augmented generator
Junda Zhu, Lingyong Yan, Haibo Shi, Dawei Yin, and Lei Sha · 2024
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Reasoning with large language models, a survey
Aske Plaat, Annie Wong, Suzan Verberne, Joost Broekens, Niki van Stein, and Thomas Back · 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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What makes large language models reason in (multi-turn) code generation?
Kunhao Zheng, Juliette Decugis, Jonas Gehring, Taco Cohen, Benjamin Negrevergne, and Gabriel Synnaeve · 2024
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Multi-level information retrieval augmented generation for knowledge-based visual question answering
Omar Adjali, Olivier Ferret, Sahar Ghannay, and Hervé Le Borgne · 2024
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Meta-rewarding language models: Self-improving alignment with llm-as-a-meta-judge
Tianhao Wu, Weizhe Yuan, Olga Golovneva, Jing Xu, Yuandong Tian, Jiantao Jiao, Jason Weston, and Sainbayar Sukhbaatar · 2024
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Corpuslm: Towards a unified language model on corpus for knowledge-intensive tasks
Xiaoxi Li, Zhicheng Dou, Yujia Zhou, and Fangchao Liu · 2024
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Improving scientific document retrieval with concept coverage-based query set generation
SeongKu Kang, Bowen Jin, Wonbin Kweon, Yu Zhang, Dongha Lee, Jiawei Han, and Hwanjo Yu · 2025
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Search-r1: Training llms to reason and leverage search engines with reinforcement learning
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Demystifying long chain-of-thought reasoning in llms
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