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cs.AI2026
Federated Agent Optimization
Qiang Yang, Zhiqiang Kou, Xueyi Zhang +6
Large language model (LLM) agents increasingly operate in private environments and accumulate valuable experience from task execution, tool use, feedback, and local knowledge. Yet…
cs.AI2026
SafeGene: Reusable Adapters for Transferable Safety Alignment
Yanghan Wang, Zhiqiang Kou, Fu Feng +2
Open-weight LLMs are increasingly fine-tuned into customized assistants, but downstream fine-tuning can weaken safety alignment and make models more vulnerable to malicious prompts…
cs.AI2026
Toward Efficient Agents: Memory, Tool learning, and Planning
Xiaofang Yang, Lijun Li, Heng Zhou +12
Recent years have witnessed increasing interest in extending large language models into agentic systems. While the effectiveness of agents has continued to improve, efficiency, whi…