18 citations · 27 across the 5 of their papers we have counts for
5 papers
Towards Graph-hop Retrieval and Reasoning in Complex Question Answering over Textual Database
Minjun Zhu, Yixuan Weng, Shizhu He +2
In Textual question answering (TQA) systems, complex questions often require retrieving multiple textual fact chains with multiple reasoning steps. While existing benchmarks are li…
Large Language Models Need Holistically Thought in Medical Conversational QA
Yixuan Weng, Bin Li, Fei Xia +5
The medical conversational question answering (CQA) system aims at providing a series of professional medical services to improve the efficiency of medical care. Despite the succes…
Mastering Symbolic Operations: Augmenting Language Models with Compiled Neural Networks
Yixuan Weng, Minjun Zhu, Fei Xia +4
Language models' (LMs) proficiency in handling deterministic symbolic reasoning and rule-based tasks remains limited due to their dependency implicit learning on textual data. To e…
Large Language Models are Better Reasoners with Self-Verification
Yixuan Weng, Minjun Zhu, Fei Xia +6
Recently, with the chain of thought (CoT) prompting, large language models (LLMs), e.g., GPT-3, have shown strong reasoning ability in several natural language processing tasks suc…
ReasonChainQA: Text-based Complex Question Answering with Explainable Evidence Chains
Minjun Zhu, Yixuan Weng, Shizhu He +2
The ability of reasoning over evidence has received increasing attention in question answering (QA). Recently, natural language database (NLDB) conducts complex QA in knowledge bas…