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20242026
most citedVision Language Models See What You Want but not What You See

2 citations · 3 across the 16 of their papers we have counts for

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cs.CV2026

EgoForge: Goal-Directed Egocentric World Simulator

Yifan Shen, Jiateng Liu, Xinzhuo Li +9

Generative world models have shown promise for simulating dynamic environments, yet egocentric video remains challenging due to rapid viewpoint changes, frequent hand-object intera…

cs.CV2026

ThinkJEPA: Empowering Latent World Models with Large Vision-Language Reasoning Model

Haichao Zhang, Yijiang Li, Shwai He +5

Recent progress in latent world models (e.g., V-JEPA2) has shown promising capability in forecasting future world states from video observations. Nevertheless, dense prediction fro…

cs.CV2026

A Very Big Video Reasoning Suite

Maijunxian Wang, Ruisi Wang, Juyi Lin +53

Rapid progress in video models has largely focused on visual quality, leaving their reasoning capabilities underexplored. Video reasoning grounds intelligence in spatiotemporally c…

cs.CV2026★ 1 cited

Egocentric Bias in Vision-Language Models

Maijunxian Wang, Yijiang Li, Bingyang Wang +6

Visual perspective taking--inferring how the world appears from another's viewpoint--is foundational to social cognition. We introduce FlipSet, a diagnostic benchmark for Level-2 v…

cs.CV2025

Vision-Language Models Mistake Head Orientation for Gaze Direction: Nonverbal Conversation Cues

Zory Zhang, Pinyuan Feng, Bingyang Wang +7

Where someone looks is a nonverbal communication cue that children and adults readily use. How well can Vision-Language Models (VLMs) infer gaze targets? To construct evaluation st…

cs.CV2025

Probing Perceptual Constancy in Large Vision-Language Models

Haoran Sun, Bingyang Wang, Suyang Yu +14

Perceptual constancy is the ability to maintain stable perceptions of objects despite changes in sensory input, such as variations in distance, angle, or lighting. This ability is…