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Zhenyu Zhang

ACL 2026×2CVPR 2026NeurIPS 2026多模态对齐与偏好效率与系统可解释性长上下文与架构
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0 一作 · 4 篇 · ACL 2026 / CVPR 2026 / NeurIPS 2026

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2026 顶会论文

4
作者位次 #4/11ACL 2026Poster· Natural Language Processing

Uncertainty-Aware Routing for Principled Alignment with M o E Dynamics

Yilong Chen · Junyuan Shang · Yuchen Feng · Zhenyu Zhang · Naibin Gu · Ziqi Wang · Tingwen Liu · Shuohuan Wang · YU SUN · hua wu · Haifeng Wang

摘要

Mixture-of-Experts (MoE) is a cornerstone for scaling LLMs, yet its training dynamics remain poorly understood, often leading to sub-optimal specialization. Moving beyond static routing, we present a systematic study of the MoE lifecycle using Helmholtz Free Energyand Router Entropy. We identify...

效率与系统对齐与偏好OpenReview 项目页
作者位次 #5/12ACL 2026Findings· Findings of ACL

Sparse Growing Transformer: Training-Time Sparse Depth Allocation via Progressive Attention Looping

Yao Chen · Yilong Chen · Yinqi Yang · Junyuan Shang · Zhenyu Zhang · Zefeng Zhang · Shuaiyi Nie · Shuohuan Wang · YU SUN · hua wu · Haifeng Wang · Tingwen Liu

摘要

Existing approaches to increasing the effective depth of Transformers predominantly rely on parameter reuse, extending computation through recursive execution.Under this paradigm, the network structure remains static along the training timeline, and additional computational depth is uniformly ass...

可解释性效率与系统长上下文与架构OpenReview 项目页

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