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cs.CL2026
Improving Few-Step Language Flows with Untied Self-Conditioning
Bocheng Li, Linli Xu
Flow-matching language models refine all token positions in parallel and can trade sampling steps for latency, yet generation quality still degrades sharply with few sampling steps…
cs.CV2026
EVA01: Unified Native 3D Understanding and Generation via Mixture-of-Transformers
Zongyuan Yang, Mingjing Yi, Wanli Ma +8
This paper addresses the challenge of integrating 3D meshes as a native modality within Multimodal Large Language Models (MLLMs). Diffusion-based large reconstruction models decoup…
cs.RO2026
Learning Native Continuation for Action Chunking Flow Policies
Yufeng Liu, Hang Yu, Juntu Zhao +9
Action chunking enables Vision Language Action (VLA) models to run in real time, but naive chunked execution often exhibits discontinuities at chunk boundaries. Real-Time Chunking…