most citedTimeBlind: A Spatio-Temporal Compositionality Benchmark for Video LLMs

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cs.CV2026

Searching Videos as Trees: Self-Correcting Agents for Grounded Long Video QA

Ce Zhang, Ziyang Wang, Yulu Pan +6

Grounded long-video question answering (Grounded LVQA) requires answering a question about a long video while localizing the short evidence interval that supports the answer. Recen…

cs.CV2026

EgoMemReason: A Memory-Driven Reasoning Benchmark for Long-Horizon Egocentric Video Understanding

Ziyang Wang, Yue Zhang, Shoubin Yu +6

Next-generation visual assistants, such as smart glasses, embodied agents, and always-on life-logging systems, must reason over an entire day or more of continuous visual experienc…

cs.CV2026

SiLVR: A Simple Language-based Video Reasoning Framework

Ce Zhang, Yan-Bo Lin, Ziyang Wang +2

Recent advances in test-time optimization have led to remarkable reasoning capabilities in Large Language Models (LLMs), enabling them to solve highly complex problems in math and…

cs.CV20261 cited

TimeBlind: A Spatio-Temporal Compositionality Benchmark for Video LLMs

Baiqi Li, Kangyi Zhao, Ce Zhang +3

Fine-grained spatio-temporal understanding is essential for video reasoning and embodied AI. Yet, while Multimodal Large Language Models (MLLMs) master static semantics, their gras…

cs.CV2025

Enhancing Visual Planning with Auxiliary Tasks and Multi-token Prediction

Ce Zhang, Yale Song, Ruta Desai +4

Visual Planning for Assistance (VPA) aims to predict a sequence of user actions required to achieve a specified goal based on a video showing the user's progress. Although recent a…

cs.CV2025

BASKET: A Large-Scale Video Dataset for Fine-Grained Skill Estimation

Yulu Pan, Ce Zhang, Gedas Bertasius

We present BASKET, a large-scale basketball video dataset for fine-grained skill estimation. BASKET contains 4,477 hours of video capturing 32,232 basketball players from all over…