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20242026
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cs.CV2026

Evaluating Time Awareness and Cross-modal Active Perception of Large Models via 4D Escape Room Task

Yurui Dong, Ziyue Wang, Shuyun Lu +5

Multimodal Large Language Models (MLLMs) have recently made rapid progress toward unified Omni models that integrate vision, language, and audio. However, existing environments lar…

cs.CV2026

Enabling Stroke-Level Structural Analysis of Hieroglyphic Scripts without Language-Specific Priors

Fuwen Luo, Zihao Wan, Ziyue Wang +6

Hieroglyphs, as logographic writing systems, encode rich semantic and cultural information within their internal structural composition. Yet, current advanced Large Language Models…

cs.CV2025

MUSEG: Reinforcing Video Temporal Understanding via Timestamp-Aware Multi-Segment Grounding

Fuwen Luo, Shengfeng Lou, Chi Chen +9

Video temporal understanding is crucial for multimodal large language models (MLLMs) to reason over events in videos. Despite recent advances in general video understanding, curren…

cs.CV2025

EscapeCraft: A 3D Room Escape Environment for Benchmarking Complex Multimodal Reasoning Ability

Ziyue Wang, Yurui Dong, Fuwen Luo +5

The rapid advancing of Multimodal Large Language Models (MLLMs) has spurred interest in complex multimodal reasoning tasks in the real-world and virtual environment, which require…

cs.CV2025

DongbaMIE: A Multimodal Information Extraction Dataset for Evaluating Semantic Understanding of Dongba Pictograms

Xiaojun Bi, Shuo Li, Junyao Xing +7

Dongba pictographic is the only pictographic script still in use in the world. Its pictorial ideographic features carry rich cultural and contextual information. However, due to th…

cs.CV2024

StreamingBench: Assessing the Gap for MLLMs to Achieve Streaming Video Understanding

Junming Lin, Zheng Fang, Chi Chen +5

The rapid development of Multimodal Large Language Models (MLLMs) has expanded their capabilities from image comprehension to video understanding. However, most of these MLLMs focu…