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Multi-hop Question Answering (QA) necessitates complex reasoning by integrating multiple pieces of information to resolve intricate questions.
The probabilistic relevance framework: BM25 and beyond
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Promptagator: Few-shot dense retrieval from 8 examples
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A survey on multi-hop question answering and generation
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Measuring and narrowing the compositionality gap in language models
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Interleaving retrieval with chain-of-thought reasoning for knowledge-intensive multi-step questions
Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, and Ashish Sabharwal. 2022a · 2022
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MuSiQue: Multihop Questions via Single-hop Question Composition
Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, and Ashish Sabharwal. 2022b · 2022
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Active retrieval augmented generation
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Replug: Retrieval-augmented black-box language models
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Answering questions by meta-reasoning over multiple chains of thought
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Iteratively Prompt Pre-trained Language Models for Chain of Thought. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing , Yoav Goldberg, Zornitsa Kozareva, and Yue Zhang (Eds.). Association for Computational Linguistics, Abu Dhabi, United Arab Emirates, 2714–2730
Boshi Wang, Xiang Deng, and Huan Sun. 2022a · 2022
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Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2022b · 2022
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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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React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2022 · 2022
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Least-to-most prompting enables complex reasoning in large language models
Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc Le, et al · 2022
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Self-rag: Learning to retrieve, generate, and critique through self-reflection
Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi. 2023 · 2023
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A survey of chain of thought reasoning: Advances, frontiers and future
Zheng Chu, Jingchang Chen, Qianglong Chen, Weijiang Yu, Tao He, Haotian Wang, Weihua Peng, Ming Liu, Bing Qin, and Ting Liu. 2023 · 2023
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Multi-hop Question Answering
Vaibhav Mavi, Anubhav Jangra, Jatowt Adam, et al · 2024
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Ming Wang, Yuanzhong Liu, Xiaoming Zhang, Songlian Li, Yijie Huang, Chi Zhang, Daling Wang, Shi Feng, and Jigang Li. 2024 · 2024
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Clasheval: Quantifying the tug-of-war between an llm’s internal prior and external evidence
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How faithful are RAG models? Quantifying the tug-of-war between RAG and LLMs’ internal prior
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Search-in-the-Chain: Interactively Enhancing Large Language Models with Search for Knowledge-intensive Tasks. In Proceedings of the ACM on Web Conference 2024 . 1362–1373
Shicheng Xu, Liang Pang, Huawei Shen, Xueqi Cheng, and Tat-Seng Chua. 2024 · 2024
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Dense text retrieval based on pretrained language models: A survey
Wayne Xin Zhao, Jing Liu, Ruiyang Ren, and Ji-Rong Wen. 2024 · 2024
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Metacognitive Retrieval-Augmented Large Language Models
Yujia Zhou, Zheng Liu, Jiajie Jin, Jian-Yun Nie, and Zhicheng Dou. 2024 · 2024
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