16 citations · 26 across the 10 of their papers we have counts for
10 papers
SKA-Bench: A Fine-Grained Benchmark for Evaluating Structured Knowledge Understanding of LLMs
Zhiqiang Liu, Enpei Niu, Yin Hua +4
Although large language models (LLMs) have made significant progress in understanding Structured Knowledge (SK) like KG and Table, existing evaluations for SK understanding are non…
OneEval: Benchmarking LLM Knowledge-intensive Reasoning over Diverse Knowledge Bases
Yongrui Chen, Zhiqiang Liu, Jing Yu +21
Large Language Models (LLMs) have demonstrated substantial progress on reasoning tasks involving unstructured text, yet their capabilities significantly deteriorate when reasoning…
SciCUEval: A Comprehensive Dataset for Evaluating Scientific Context Understanding in Large Language Models
Jing Yu, Yuqi Tang, Kehua Feng +8
Large Language Models (LLMs) have shown impressive capabilities in contextual understanding and reasoning. However, evaluating their performance across diverse scientific domains r…
KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation
Lei Liang, Mengshu Sun, Zhengke Gui +16
The recently developed retrieval-augmented generation (RAG) technology has enabled the efficient construction of domain-specific applications. However, it also has limitations, inc…
TrustUQA: A Trustful Framework for Unified Structured Data Question Answering
Wen Zhang, Long Jin, Yushan Zhu +6
Natural language question answering (QA) over structured data sources such as tables and knowledge graphs have been widely investigated, especially with Large Language Models (LLMs…
InBox: Recommendation with Knowledge Graph using Interest Box Embedding
Zezhong Xu, Yincen Qu, Wen Zhang +2
Knowledge graphs (KGs) have become vitally important in modern recommender systems, effectively improving performance and interpretability. Fundamentally, recommender systems aim t…
Prompt-fused framework for Inductive Logical Query Answering
Zezhong Xu, Peng Ye, Lei Liang +2
Answering logical queries on knowledge graphs (KG) poses a significant challenge for machine reasoning. The primary obstacle in this task stems from the inherent incompleteness of…
Knowledgeable Preference Alignment for LLMs in Domain-specific Question Answering
Yichi Zhang, Zhuo Chen, Yin Fang +4
Deploying large language models (LLMs) to real scenarios for domain-specific question answering (QA) is a key thrust for LLM applications, which poses numerous challenges, especial…
Reliable Academic Conference Question Answering: A Study Based on Large Language Model
Zhiwei Huang, Juan Li, Long Jin +6
As the development of academic conferences fosters global scholarly communication, researchers consistently need to obtain accurate and up-to-date information about academic confer…
Making Large Language Models Perform Better in Knowledge Graph Completion
Yichi Zhang, Zhuo Chen, Lingbing Guo +3
Large language model (LLM) based knowledge graph completion (KGC) aims to predict the missing triples in the KGs with LLMs. However, research about LLM-based KGC fails to sufficien…