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cs.AI2026
Multi-Agent Agentic Graph Learning via Structural Signatures
Liang Qu, Jianxin Li, Hua Wang
Agentic graph learning (AGL) has recently achieved promising results on graph reasoning tasks, where an agent powered by a large language model (LLM) sequentially samples the graph…
cs.IR2026
Federated Learning and Unlearning for Recommendation with Personalized Data Sharing
Liang Qu, Jianxin Li, Wei Yuan +4
Federated recommender systems (FedRS) have emerged as a paradigm for protecting user privacy by keeping interaction data on local devices while coordinating model training through…
cs.CL2026
QA-Merging: Query-Adaptive Reasoning via Layer Selective Model Merging
Zhaofeng Zhong, Wei Yuan, Tong Chen +4
Recent large reasoning models (LRMs) have achieved strong performance on complex reasoning tasks by generating a long chain-of-thought (Long-CoT). However, such lengthy reasoning i…