10 citations · 11 across the 5 of their papers we have counts for
8 papers · 1 filter
CE-GOCD: Central Entity-Guided Graph Optimization for Community Detection to Augment LLM Scientific Question Answering
Jiayin Lan, Jiaqi Li, Baoxin Wang +5
Large Language Models (LLMs) are increasingly used for question answering over scientific research papers. Existing retrieval augmentation methods often rely on isolated text chunk…
Graph Reasoning Paradigm: Structured and Symbolic Reasoning with Topology-Aware Reinforcement Learning for Large Language Models
Runxuan Liu, Xianhao Ou, Xinyan Ma +13
Long Chain-of-Thought (LCoT), achieved by Reinforcement Learning with Verifiable Rewards (RLVR), has proven effective in enhancing the reasoning capabilities of Large Language Mode…
NLP-AKG: Few-Shot Construction of NLP Academic Knowledge Graph Based on LLM
Jiayin Lan, Jiaqi Li, Baoxin Wang +4
Large language models (LLMs) have been widely applied in question answering over scientific research papers. To enhance the professionalism and accuracy of responses, many studies…
Ontology-Guided Reverse Thinking Makes Large Language Models Stronger on Knowledge Graph Question Answering
Runxuan Liu, Bei Luo, Jiaqi Li +5
Large language models (LLMs) have shown remarkable capabilities in natural language processing. However, in knowledge graph question answering tasks (KGQA), there remains the issue…
SparkRA: A Retrieval-Augmented Knowledge Service System Based on Spark Large Language Model
Dayong Wu, Jiaqi Li, Baoxin Wang +10
Large language models (LLMs) have shown remarkable achievements across various language tasks.To enhance the performance of LLMs in scientific literature services, we developed the…
DADgraph: A Discourse-aware Dialogue Graph Neural Network for Multiparty Dialogue Machine Reading Comprehension
Jiaqi Li, Ming Liu, Zihao Zheng +4
Multiparty Dialogue Machine Reading Comprehension (MRC) differs from traditional MRC as models must handle the complex dialogue discourse structure, previously unconsidered in trad…