22 citations · 25 across the 8 of their papers we have counts for
8 papers
Pandora: Leveraging Code-driven Knowledge Transfer for Unified Structured Knowledge Reasoning
Yongrui Chen, Junhao He, Linbo Fu +10
Unified Structured Knowledge Reasoning (USKR) aims to answer natural language questions by using structured sources such as tables, databases, and knowledge graphs in a unified way…
Pandora: A Code-Driven Large Language Model Agent for Unified Reasoning Across Diverse Structured Knowledge
Yongrui Chen, Junhao He, Linbo Fu +10
Unified Structured Knowledge Reasoning (USKR) aims to answer natural language questions (NLQs) by using structured sources such as tables, databases, and knowledge graphs in a unif…
UniHGKR: Unified Instruction-aware Heterogeneous Knowledge Retrievers
Dehai Min, Zhiyang Xu, Guilin Qi +2
Existing information retrieval (IR) models often assume a homogeneous structure for knowledge sources and user queries, limiting their applicability in real-world settings where re…
MATEval: A Multi-Agent Discussion Framework for Advancing Open-Ended Text Evaluation
Yu Li, Shenyu Zhang, Rui Wu +5
Recent advancements in generative Large Language Models(LLMs) have been remarkable, however, the quality of the text generated by these models often reveals persistent issues. Eval…
HeGTa: Leveraging Heterogeneous Graph-enhanced Large Language Models for Few-shot Complex Table Understanding
Rihui Jin, Yu Li, Guilin Qi +7
Table understanding (TU) has achieved promising advancements, but it faces the challenges of the scarcity of manually labeled tables and the presence of complex table structures.To…
Exploring the Impact of Table-to-Text Methods on Augmenting LLM-based Question Answering with Domain Hybrid Data
Dehai Min, Nan Hu, Rihui Jin +8
Augmenting Large Language Models (LLMs) for Question Answering (QA) with domain specific data has attracted wide attention. However, domain data often exists in a hybrid format, in…
An Empirical Study of Pre-trained Language Models in Simple Knowledge Graph Question Answering
Nan Hu, Yike Wu, Guilin Qi +4
Large-scale pre-trained language models (PLMs) such as BERT have recently achieved great success and become a milestone in natural language processing (NLP). It is now the consensu…
Can ChatGPT Replace Traditional KBQA Models? An In-depth Analysis of the Question Answering Performance of the GPT LLM Family
Yiming Tan, Dehai Min, Yu Li +4
ChatGPT is a powerful large language model (LLM) that covers knowledge resources such as Wikipedia and supports natural language question answering using its own knowledge. Therefo…