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cs.AI2026
IronLLM: Forging Compact Edge-Native Language Models for Real-Time Embodied Intelligence
Changdi Yang, Fengquan Jiao, Haochih Lin +14
We present IronLLM-0.6B, a 654M-parameter language model designed for efficient on-device inference. IronLLM-0.6B combines a hybrid attention architecture with X-MTP, a lightweight…
cs.AI2025
Advancing AI-Scientist Understanding: Multi-Agent LLMs with Interpretable Physics Reasoning
Yinggan Xu, Hana Kimlee, Yijia Xiao +1
Large Language Models (LLMs) are playing an increasingly important role in physics research by assisting with symbolic manipulation, numerical computation, and scientific reasoning…