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20242026
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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.CV2026

SVAG-Bench: A Large-Scale Benchmark for Multi-Instance Spatio-temporal Video Action Grounding

Tanveer Hannan, Shuaicong Wu, Mark Weber +6

A truly capable AI system must do more than detect objects or recognize activities in isolation. It must form unified, grounded representations of who is acting, what they are doin…

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…

cs.CV2025

DocSLM: A Small Vision-Language Model for Long Multimodal Document Understanding

Tanveer Hannan, Dimitrios Mallios, Parth Pathak +5

Large Vision-Language Models (LVLMs) have demonstrated strong multimodal reasoning capabilities on long and complex documents. However, their high memory footprint makes them impra…

cs.CV2025

Human Uncertainty-Aware Data Selection and Automatic Labeling in Visual Question Answering

Jian Lan, Zhicheng Liu, Udo Schlegel +5

Large vision-language models (VLMs) achieve strong performance in Visual Question Answering but still rely heavily on supervised fine-tuning (SFT) with massive labeled datasets, wh…