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20242026
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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.CV2026

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.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.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…