3 papers
cs.LG2026
GroupMask: Layer-Adaptive Group-wise Sparsity for Semi-Structured LLM Pruning
Zhengao Li, Shuoqiu Li, Xiaofang Zhang +7
Semi-structured pruning compresses large language models (LLMs) while keeping a regular sparse structure, but the prevailing N:M pattern fixes the same local sparsity ratio in ever…
cs.LG2026
MUGEN: A Unified Framework for Efficient Motion Understanding and Generation
Zhankai Ye, Yukai Jin, Bingyang Wei +5
Grounding human motion in language, and language in motion, is a central step toward physical AI systems that can understand, generate, and communicate human behavior. Unified moti…
cs.CV2026
GeoMotionGPT: Geometry-Aligned Motion Understanding with Large Language Models
Zhankai Ye, Bofan Li, Yukai Jin +5
Discrete motion tokenization has recently enabled Large Language Models (LLMs) to serve as versatile backbones for motion understanding and motion-language reasoning. However, exis…