AAAI 2026technical0 citations
TGCA-LLM: Time-Aware Graph-Text Contrastive Alignment for Enhancing LLMs in Temporal Knowledge Graph Completion
Zexuan Wan, Bo Wang, Kuofei Fang, Bin Wu
Abstract
Temporal Knowledge Graph Completion (TKGC) aims to infer missing facts by modeling historical events and latent temporal dependencies in Temporal Knowledge Graphs (TKGs). Recently, TKGC methods that integrate graph embeddings into Large Language Models (LLMs) have shown great promise by leveraging the structural information of TKGs together with the powerful reasoning capabilities of LLMs. However, these embedding-based methods are limited by suboptimal graph representations due to noise and long-tail issues in real-world scenarios, and insufficient cross-modal alignment between graph and language, hindering LLMs
BibTeX
@inproceedings{aaai2026_tgcallmtimeaware,
title = {TGCA-LLM: Time-Aware Graph-Text Contrastive Alignment for Enhancing LLMs in Temporal Knowledge Graph Completion},
author = {Zexuan Wan and Bo Wang and Kuofei Fang and Bin Wu},
booktitle = {AAAI 2026},
year = {2026}
}