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20232026
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cs.CV2026

Vision-Language-Guided Pseudo-Labels for Unsupervised Domain Adaptation in Semantic Segmentation for Waste Sorting

Udo Schlegel, Shubhangi, Gabriel Dax +3

Obtaining labeled data for semantic segmentation in applied settings (e.g., autonomous driving, industrial waste sorting) is expensive and often infeasible at scale. We present a c…

cs.CV2026

TunerDiT: Training-free Progressive Steering of Diffusion Transformer for Multi-Event Video Generation

Ruotong Liao, Guowen Huang, Qing Cheng +6

Text-to-video (T2V) generation faces challenging questions when generating videos with long horizons containing multiple events. Inspired by the intrinsics of the diffusion process…

cs.CL2026

Beyond Input Understanding: Diagnosing Multilingual Mathematical Reasoning with Directed Acyclic Trace Graphs

Jiaqiao Zhang, Zhoujun Li, Zhuojun Li +6

Large reasoning models (LRMs) achieve strong mathematical reasoning performance in English, but remain much less reliable in many low- and medium-resource languages. This gap is of…

cs.CV2026

NICE FACT: Diagnosing and Calibrating VLMs in Quantitative Reasoning for Kinematic Physics

Jian Lan, Zhicheng Liu, Xinpeng Wang +5

The ability to derive precise spatial and physical insights is a cornerstone of vision-language models (VLMs), yet their poor performances in related spatial intelligence tasks suc…

cs.CV2026

ForgeVLA: Federated Vision-Language-Action Learning without Language Annotations

Yuhao Zhou, Yunpeng Zhu, Yang Zhou +7

Vision-Language-Action (VLA) models hold great promise for general-purpose robotic intelligence, yet scaling up such models is severely bottlenecked by the high cost of acquiring a…