Author

Xiangyu Li

Institue for AI Industry Research (AIR), Tsinghua University

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#large language models Nov 2026

DWI: Efficient On-Device LLM Decoding Through Dynamic Width Selection on Nested Models

Deploying large language models (LLMs) on resource-constrained mobile devices remains a significant challenge due to memory limitations and high I/O overhead. While existing dynamic sparsity methods reduce computation costs, they often suffer from inefficient loading patterns that degrade I/O throughput. To address thi...

Wei-Ning Chen, Yong-Heng Deng, Xiang Wang et al. · IEEE Transactions on Mobile... · 0 citations

Preprint Aug 2026

Zeva: In-Context Causal Learning for Generalizable Embodied Manipulation

Zeva is presented, the first framework that enables in-context learning from a robot's own physical interaction experience while keeping the policy model frozen, and achieves the best performance among the compared frontier VLAs and WAMs and enables self-evolution during deployment without gradient updates.

Fu Chen, Xin Ding, Bing-Jia Huang et al. · 3 citations

Preprint Aug 2026

Zetta $\zeta$: An Efficient Closed-Loop Embodied Harness for Self-Evolving Physical Intelligence

Zetta is presented, a closed-loop embodied harness that evolves code-based runtime critics and recovery skills online while keeping the base policy frozen, and shows that closed-loop harness self-evolution opens a scaling path for reliable physical intelligence.

Xin Ding, Liang Mi, Ming-Zhe Huang et al. · 7 citations · ⚡1