2 citations · 6 across the 7 of their papers we have counts for
8 papers
Remember Before You're Asked: MemDream for Self-Probing Memory Evolution
Mingfei Lu, Mengjia Wu, Runsong Jia +2
Memory is essential for enabling LLM-based agents to maintain coherent, personalized behavior over long-horizon interactions. However, existing memory systems share a fundamental l…
Evidence-Aligned Entity Verification for Hallucination Detection in Retrieval-Augmented Generation
Runsong Jia, Zhen Fang, Mengjia Wu +2
Hallucination detection is crucial for large language models (LLMs), as hallucinated content creates significant barriers in applications requiring factual accuracy. Current detect…
Agent-Enhanced Heterogeneous Graph RAG for Academic Question Answering
Runsong Jia, Mengjia Wu, Ying Ding +2
Academic question answering requires reasoning over heterogeneous scholarly graphs, where queries range from simple attribute lookups to multi-hop inference across author--paper--v…
Forget Less, Generalize More: Unifying Temporal and Structural Adaptation for Dynamic Graphs
Qian Chang, Ciprian Doru Giurcaneanu, Runsong Jia +6
Representation learning on dynamic graphs requires capturing complex dependencies that evolve across both time and structure. Existing approaches typically adopt fixed temporal dec…
AI-Enhanced Multi-Dimensional Measurement of Technological Convergence through Heterogeneous Graph and Semantic Learning
Siming Deng, Runsong Jia, Chunjuan Luan +2
Technological convergence refers to the phenomenon where boundaries between technological areas and disciplines are increasingly blurred. It enables the integration of previously d…
HetGCoT: Heterogeneous Graph-Enhanced Chain-of-Thought LLM Reasoning for Academic Question Answering
Runsong Jia, Mengjia Wu, Ying Ding +2
Academic question answering (QA) in heterogeneous scholarly networks presents unique challenges requiring both structural understanding and interpretable reasoning. While graph neu…
Graph Retention Networks for Dynamic Graphs
Qian Chang, Xia Li, Xiufeng Cheng +4
In this paper, we propose Graph Retention Networks (GRNs) as a unified architecture for deep learning on dynamic graphs. The GRN extends the concept of retention into dynamic graph…
Leveraging Large Language Models for Semantic Query Processing in a Scholarly Knowledge Graph
Runsong Jia, Bowen Zhang, Sergio J. Rodríguez Méndez +1
The proposed research aims to develop an innovative semantic query processing system that enables users to obtain comprehensive information about research works produced by Compute…