Nov 7, 2023 · In this work, we investigate constructing and leveraging extracted semantic structures (graphs) for multi-hop question answering, especially the reasoning ...

Dec 6, 2023 · In our approach, we leverage semantic graphs extracted from documents, which guide reasoning processes and help accurately find the answer node.

Oct 7, 2023 · In this work, we investigate constructing and leveraging extracted semantic structures (graphs) for multi-hop question answering, especially the reasoning�...

This work investigates constructing and leveraging extracted semantic structures (graphs) for multi-hop question answering, especially the reasoning process ...

Multi-hop question answering (QA) involves answering questions that require reasoning over multiple pieces of information, often spread across different parts ...

Multi-hop Question Answering (QA) necessitates complex reasoning by integrating multiple pieces of information to resolve intricate questions.

May 31, 2024 · The ability to answer multi-hop questions and perform multi step reasoning can significantly improve the utility of NLP systems. Consequently, ...

The goal of MHQA is to predict the correct answer to a question that requires multiple reasoning 'hops' across given contexts (text, table, knowledge graph etc) ...

Neural models, including large language models (LLMs), achieve superior performance on logical reasoning tasks such as question answering.

This study presents a new multi-hop QA dataset, called 2WikiMultiHopQA, which uses structured and unstructured data and introduces the evidence information.