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From the 1 of 7 linked papers with an AI index.

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20242026
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cs.CV2026

VideoRAE: Taming Video Foundation Models for Generative Modeling via Representation Autoencoders

Zhihao Xie, Junfeng Wu, Xinting Hu +2

VideoRAE is a representation autoencoder that leverages frozen video foundation model features to create compact, generation‑friendly video latents, supporting both continuous diff…

cs.CV2026

Mitigating Object Hallucinations via Sentence-Level Early Intervention

Shangpin Peng, Senqiao Yang, Li Jiang +1

Multimodal large language models (MLLMs) have revolutionized cross-modal understanding but continue to struggle with hallucinations - fabricated content contradicting visual inputs…

cs.CV2026

FlashVID: Efficient Video Large Language Models via Training-free Tree-based Spatiotemporal Token Merging

Ziyang Fan, Keyu Chen, Ruilong Xing +3

Although Video Large Language Models (VLLMs) have shown remarkable capabilities in video understanding, they are required to process high volumes of visual tokens, causing signific…

cs.CV2025

Memory Forcing: Spatio-Temporal Memory for Consistent Scene Generation on Minecraft

Junchao Huang, Xinting Hu, Boyao Han +4

Autoregressive video diffusion models have proved effective for world modeling and interactive scene generation, with Minecraft gameplay as a representative application. To faithfu…

cs.CV2024

Unified Language-driven Zero-shot Domain Adaptation

Senqiao Yang, Zhuotao Tian, Li Jiang +1

This paper introduces Unified Language-driven Zero-shot Domain Adaptation (ULDA), a novel task setting that enables a single model to adapt to diverse target domains without explic…