Author

Su Lu

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#artificial intelligence Preprint Sep 2026

IronLLM: Forging Compact Edge-Native Language Models for Real-Time Embodied Intelligence

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 shared-KV multi-token prediction design that eliminates per-depth KV-cache replay and employs a lightweight verification head for rollback-...

Chang-Di Yang, Feng-Quan Jiao, Hao-Chih Lin et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Routing Drift Alone Does Not Diagnose Failure in Merged MoE LLMs

Model merging efficiently combines specialized large language models (LLMs) without joint retraining, but can substantially alter expert routing in Mixture-of-Experts (MoE) models. Such \emph{routing drift} is often interpreted as routing failure, raising a fundamental question that remains unclear: \emph{does routing...

Yuan-Yi Wang, Yang-Gan Gu, Su Lu et al. · 0 citations