47 citations · 61 across the 11 of their papers we have counts for
11 papers
After Retrieval, Before Generation: Enhancing the Trustworthiness of Large Language Models in Retrieval-Augmented Generation
Xinbang Dai, Huikang Hu, Yuncheng Hua +5
Retrieval-augmented generation (RAG) is a promising paradigm, yet its trustworthiness remains a critical concern. A major vulnerability arises prior to generation: models often fai…
CoTKR: Chain-of-Thought Enhanced Knowledge Rewriting for Complex Knowledge Graph Question Answering
Yike Wu, Yi Huang, Nan Hu +4
Recent studies have explored the use of Large Language Models (LLMs) with Retrieval Augmented Generation (RAG) for Knowledge Graph Question Answering (KGQA). They typically require…
Let's Negotiate! A Survey of Negotiation Dialogue Systems
Haolan Zhan, Yufei Wang, Tao Feng +7
Negotiation is a crucial ability in human communication. Recently, there has been a resurgent research interest in negotiation dialogue systems, whose goal is to create intelligent…
Large Language Models Can Better Understand Knowledge Graphs Than We Thought
Xinbang Dai, Yuncheng Hua, Tongtong Wu +3
When we integrate factual knowledge from knowledge graphs (KGs) into large language models (LLMs) to enhance their performance, the cost of injection through training increases wit…
SocialDial: A Benchmark for Socially-Aware Dialogue Systems
Haolan Zhan, Zhuang Li, Yufei Wang +10
Dialogue systems have been widely applied in many scenarios and are now more powerful and ubiquitous than ever before. With large neural models and massive available data, current…
Dialog-to-Actions: Building Task-Oriented Dialogue System via Action-Level Generation
Yuncheng Hua, Xiangyu Xi, Zheng Jiang +4
End-to-end generation-based approaches have been investigated and applied in task-oriented dialogue systems. However, in industrial scenarios, existing methods face the bottlenecks…
Let's Negotiate! A Survey of Negotiation Dialogue Systems
Haolan Zhan, Yufei Wang, Tao Feng +5
Negotiation is one of the crucial abilities in human communication, and there has been a resurgent research interest in negotiation dialogue systems recently, which goal is to empo…
A Low-Cost, Controllable and Interpretable Task-Oriented Chatbot: With Real-World After-Sale Services as Example
Xiangyu Xi, Chenxu Lv, Yuncheng Hua +5
Though widely used in industry, traditional task-oriented dialogue systems suffer from three bottlenecks: (i) difficult ontology construction (e.g., intents and slots); (ii) poor c…
Formal Query Building with Query Structure Prediction for Complex Question Answering over Knowledge Base
Yongrui Chen, Huiying Li, Yuncheng Hua +1
Formal query building is an important part of complex question answering over knowledge bases. It aims to build correct executable queries for questions. Recent methods try to rank…
Less is More: Data-Efficient Complex Question Answering over Knowledge Bases
Yuncheng Hua, Yuan-Fang Li, Guilin Qi +3
Question answering is an effective method for obtaining information from knowledge bases (KB). In this paper, we propose the Neural-Symbolic Complex Question Answering (NS-CQA) mod…
Few-Shot Complex Knowledge Base Question Answering via Meta Reinforcement Learning
Yuncheng Hua, Yuan-Fang Li, Gholamreza Haffari +2
Complex question-answering (CQA) involves answering complex natural-language questions on a knowledge base (KB). However, the conventional neural program induction (NPI) approach e…