5 papers
Strikingness-Aware Evaluation for Temporal Knowledge Graph Reasoning
Rikui Huang, Shengzhe Zhang, Wei Wei
Temporal Knowledge Graph Reasoning (TKGR) aims at inferring missing (especially future) events from historical data. Current evaluation in TKGR uniformly weights all events, ignori…
Beyond Static Summarization: Proactive Memory Extraction for LLM Agents
Chengyuan Yang, Zequn Sun, Wei Wei +1
Memory management is vital for LLM agents to handle long-term interaction and personalization. Most research focuses on how to organize and use memory summary, but often overlooks…
ComoRAG: A Cognitive-Inspired Memory-Organized RAG for Stateful Long Narrative Reasoning
Juyuan Wang, Rongchen Zhao, Wei Wei +5
Narrative comprehension on long stories and novels has been a challenging domain attributed to their intricate plotlines and entangled, often evolving relations among characters an…
Avoiding Knowledge Edit Skipping in Multi-hop Question Answering with Guided Decomposition
Yi Liu, Xiangrong Zhu, Xiangyu Liu +2
In a rapidly evolving world where information updates swiftly, knowledge in large language models (LLMs) becomes outdated quickly. Retraining LLMs is not a cost-effective option, m…
Large Language Models-guided Dynamic Adaptation for Temporal Knowledge Graph Reasoning
Jiapu Wang, Kai Sun, Linhao Luo +5
Temporal Knowledge Graph Reasoning (TKGR) is the process of utilizing temporal information to capture complex relations within a Temporal Knowledge Graph (TKG) to infer new knowled…