activity
20232026
most citedGraph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

1 citations · 1 across the 11 of their papers we have counts for

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cs.AI2026

TIDE: Trajectory-based Diagnostic Evaluation of Test-Time Improvement in LLM Agents

Hang Yan, Xinyu Che, Fangzhi Xu +7

Recent advances in autonomous LLM agents demonstrate their ability to improve performance through iterative interaction with the environment. We define this paradigm as Test-Time I…

cs.AI2026

Towards Efficient and Robust Linguistic Emotion Diagnosis for Mental Health via Multi-Agent Instruction Refinement

Jian Zhang, Zhangqi Wang, Zhiyuan Wang +5

Linguistic expressions of emotions such as depression, anxiety, and trauma-related states are pervasive in clinical notes, counseling dialogues, and online mental health communitie…

cs.AI2026

-Bench: Benchmarking Memory-Driven Scientific Reasoning via Anchor and Attractor Activation

Jian Zhang, Yu He, Zhiyuan Wang +5

Scientific reasoning relies not only on logical inference but also on activating prior knowledge and experiential structures. Memory can efficiently reuse knowledge and enhance rea…

cs.AI2026

MAXS: Meta-Adaptive Exploration with LLM Agents

Jian Zhang, Zhiyuan Wang, Zhangqi Wang +7

Large Language Model (LLM) Agents exhibit inherent reasoning abilities through the collaboration of multiple tools. However, during agent inference, existing methods often suffer f…

cs.AI2025

Towards Unified Neurosymbolic Reasoning on Knowledge Graphs

Qika Lin, Fangzhi Xu, Hao Lu +5

Knowledge Graph (KG) reasoning has received significant attention in the fields of artificial intelligence and knowledge engineering, owing to its ability to autonomously deduce ne…

cs.AI2025

GKG-LLM: A Unified Framework for Generalized Knowledge Graph Construction

Jian Zhang, Bifan Wei, Shihao Qi +3

The construction of Generalized Knowledge Graph (GKG), including knowledge graph, event knowledge graph and commonsense knowledge graph, is fundamental for various natural language…