Reinforcement Learning for Conversational Question Answering over Knowledge Graph

2024-01-16 · Mi Wu

Conversational question answering (ConvQA) over law knowledge bases (KBs) involves answering multi-turn natural language questions about law and hope to find answers in the law knowledge base. Despite many methods have been proposed. Existing law knowledge base ConvQA model assume that the input question is clear and can perfectly reflect user's intention. However, in real world, the input questions are noisy and inexplict. This makes the model hard to find the correct answer in the law knowledge bases. In this paper, we try to use reinforcement learning to solve this problem. The reinforcement learning agent can automatically learn how to find the answer based on the input question and the conversation history, even when the input question is inexplicit. We test the proposed method on several real world datasets and the results show the effectivenss of the proposed model.

📄 PDF Abstract BibTeX arXiv:2401.08460

Code (0)

등록된 구현이 없습니다.

Tasks

Conversational Question Answering Question Answering reinforcement-learning Reinforcement Learning

Methods 이 논문이 사용한 방법론

BASE 설명 없음

Reinforcement Learning from Reformulations in Conversational Question Answering over Knowledge Graphs

2021-05-11 · Magdalena Kaiser, Rishiraj Saha Roy, Gerhard Weikum

The rise of personal assistants has made conversational question answering (ConvQA) a very popular mechanism for user-system interaction. State-of-the-art methods for ConvQA over knowledge graphs (KGs) can only learn fro…

Conversational Question Answering Knowledge Graphs Question Answering reinforcement-learning+1

Conversational Question Answering with Reformulations over Knowledge Graph

2023-12-27 · Lihui Liu, Blaine Hill, Boxin Du, Fei Wang 외

Conversational question answering (convQA) over knowledge graphs (KGs) involves answering multi-turn natural language questions about information contained in a KG. State-of-the-art methods of ConvQA often struggle with …

Conversational Question Answering Knowledge Graphs Question Answering Reinforcement Learning (RL)

MMCoQA: Conversational Question Answering over Text, Tables, and Images

2022-05-01 · ACL 2022 5 · Yongqi Li, Wenjie Li, Liqiang Nie

The rapid development of conversational assistants accelerates the study on conversational question answering (QA). However, the existing conversational QA systems usually answer users’ questions with a single knowledge …

Benchmarking Conversational Question Answering Question Answering Retrieval

Integrating Question Rewrites in Conversational Question Answering: A Reinforcement Learning Approach

2022-05-01 · ACL 2022 5 · Etsuko Ishii, Bryan Wilie, Yan Xu, Samuel Cahyawijaya 외

Resolving dependencies among dialogue history is one of the main obstacles in the research on conversational question answering (QA). The conversational question rewrites (QR) task has been shown to be effective to solve…

Conversational Question Answering Question Answering reinforcement-learning Reinforcement Learning (RL)

Ask to Learn: A Study on Curiosity-driven Question Generation

2019-11-08 · COLING 2020 8 · Thomas Scialom, Jacopo Staiano

We propose a novel text generation task, namely Curiosity-driven Question Generation. We start from the observation that the Question Generation task has traditionally been considered as the dual problem of Question Answ…

Conversational Question Answering Machine Reading Comprehension Question Answering Question Generation+4