BeamAggR: Beam Aggregation Reasoning over Multi-source Knowledge for
Multi-hop Question Answering

BeamAggR: Beam Aggregation Reasoning over Multi-source Knowledge for Multi-hop Question Answering

28 June 2024

Haotian Wang

Bing Qin

Papers citing "BeamAggR: Beam Aggregation Reasoning over Multi-source Knowledge for Multi-hop Question Answering"

5 / 5 papers shown

Title
Chain-of-Knowledge: Grounding Large Language Models via Dynamic Knowledge Adapting over Heterogeneous Sources Xingxuan Li Ruochen Zhao Yew Ken Chia Bosheng Ding Shafiq R. Joty Soujanya Poria Lidong Bing HILM BDL LRM 79 85 0 22 May 2023
Generate rather than Retrieve: Large Language Models are Strong Context Generators W. Yu Dan Iter Shuohang Wang Yichong Xu Mingxuan Ju Soumya Sanyal Chenguang Zhu Michael Zeng Meng-Long Jiang RALM AIMat 221 318 0 21 Sep 2022
Large Language Models are Zero-Shot Reasoners Takeshi Kojima S. Gu Machel Reid Yutaka Matsuo Yusuke Iwasawa ReLM LRM 291 4,048 0 24 May 2022
Self-Consistency Improves Chain of Thought Reasoning in Language Models Xuezhi Wang Jason W. Wei Dale Schuurmans Quoc Le Ed H. Chi Sharan Narang Aakanksha Chowdhery Denny Zhou ReLM BDL LRM AI4CE 297 3,163 0 21 Mar 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 303 11,730 0 04 Mar 2022