5 citations · 5 across the 5 of their papers we have counts for
4 papers · 1 filter
Self-Correction Distillation for Structured Data Question Answering
Yushan Zhu, Wen Zhang, Long Jin +8
Structured data question answering (QA), including table QA, Knowledge Graph (KG) QA, and temporal KG QA, is a pivotal research area. Advances in large language models (LLMs) have…
KAG-Thinker: Interactive Thinking and Deep Reasoning in LLMs via Knowledge-Augmented Generation
Dalong Zhang, Jun Xu, Jun Zhou +16
In this paper, we introduce KAG-Thinker, which upgrade KAG to a multi-turn interactive thinking and deep reasoning framework powered by a dedicated parameter-light large language m…
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…
Efficient Knowledge Infusion via KG-LLM Alignment
Zhouyu Jiang, Ling Zhong, Mengshu Sun +5
To tackle the problem of domain-specific knowledge scarcity within large language models (LLMs), knowledge graph-retrievalaugmented method has been proven to be an effective and ef…