4 citations · 4 across the 6 of their papers we have counts for
6 papers
TKG-Thinker: Towards Dynamic Reasoning over Temporal Knowledge Graphs via Agentic Reinforcement Learning
Zihao Jiang, Miao Peng, Zhenyan Shan +5
Temporal knowledge graph question answering (TKGQA) aims to answer time-sensitive questions by leveraging temporal knowledge bases. While Large Language Models (LLMs) demonstrate s…
Towards Explainable Temporal Reasoning in Large Language Models: A Structure-Aware Generative Framework
Zihao Jiang, Ben Liu, Miao Peng +4
While large language models (LLMs) show great potential in temporal reasoning, most existing work focuses heavily on enhancing performance, often neglecting the explainable reasoni…
Rewarding Graph Reasoning Process makes LLMs more Generalized Reasoners
Miao Peng, Nuo Chen, Zongrui Suo +1
Despite significant advancements in Large Language Models (LLMs), developing advanced reasoning capabilities in LLMs remains a key challenge. Process Reward Models (PRMs) have demo…
Deja vu: Contrastive Historical Modeling with Prefix-tuning for Temporal Knowledge Graph Reasoning
Miao Peng, Ben Liu, Wenjie Xu +3
Temporal Knowledge Graph Reasoning (TKGR) is the task of inferring missing facts for incomplete TKGs in complex scenarios (e.g., transductive and inductive settings), which has bee…
Pre-trained Language Model with Prompts for Temporal Knowledge Graph Completion
Wenjie Xu, Ben Liu, Miao Peng +2
Temporal Knowledge graph completion (TKGC) is a crucial task that involves reasoning at known timestamps to complete the missing part of facts and has attracted more and more atten…
SMiLE: Schema-augmented Multi-level Contrastive Learning for Knowledge Graph Link Prediction
Miao Peng, Ben Liu, Qianqian Xie +3
Link prediction is the task of inferring missing links between entities in knowledge graphs. Embedding-based methods have shown effectiveness in addressing this problem by modeling…