3 papers
cs.CV2026
IndusAgent: Reinforcing Open-Vocabulary Industrial Anomaly Detection with Agentic Tools
Rongbin Tan, Fangfang Lin, Zhenlong Yuan +10
Multimodal large language models (MLLMs) have shown remarkable capability in bridging visual perception and textual reasoning, enabling zero-shot understanding across diverse indus…
cs.LG2026
Federated Nested Learning: Collaborative Training of Self-Referential Memories for Test-Time Adaptation
Hong Chen, Pengcheng Wu, Yuanguo Lin +4
We rethink Federated Learning (FL) from a nested learning perspective, framing the core challenge as how to collaboratively learn optimization rules, not just static models, to tac…
cs.CR2025
A Survey on Data Security in Large Language Models
Kang Chen, Xiuze Zhou, Yuanguo Lin +4
Large Language Models (LLMs), now a foundation in advancing natural language processing, power applications such as text generation, machine translation, and conversational systems…