Author

Bin-Bin Chen

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Preprint Nov 2026

CARE-FL: Federated Fine-Tuning of Multimodal LLMs in Resource-Constrained Edge Networks

Domain-specific adaptation of Multimodal Large Language Models (MLLMs) in privacy-sensitive edge environments requires federated fine-tuning, yet client selection remains challenging due to heterogeneous multimodal data and modality availability, dynamic system conditions, and evolving client utility during training. W...

Tian-Qi Zong, Bao-Sheng Li, Nuo-Cheng Yang et al. · 0 citations

#artificial intelligence Feb 2026

Reasoning and Tool-use Compete in Agentic RL:From Quantifying Interference to Disentangled Tuning

This paper proposes Disentangled Action--Reasoning Tuning (DART), a simple and efficient framework that explicitly decouples parameter updates for reasoning and tool use via separate low-rank adaptation modules, further supporting the finding of capability interference under shared optimization.

Yu Li, Ming-Yang Yi, Xiu‐Qing Li et al. · arXiv.org · 15 citations · ⚡1