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20242026
most citedVISA: Reasoning Video Object Segmentation via Large Language Models

2 citations · 4 across the 16 of their papers we have counts for

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15 papers · 1 filter

cs.CV2026

SPAR: Semantic-Pixel Self-Alignment and Adaptive Routing for Unified Multimodal Models

Hongxiang Li, Hongxu Chen, Chenyang Zhu +5

Multimodal Large Language Models (MLLMs) have achieved remarkable success in visual understanding but remain constrained in visual generation due to the fundamental feature discrep…

cs.CV2026

Impostor: An Agent-Curated Benchmark for Realistic AIGC Manipulation Localization

Zhenliang Li, Yutao Hu, Qixiong Wang +5

Recent advances in generative image editing have improved the realism and controllability of localized image manipulation, raising new challenges for image manipulation detection a…

cs.CV2026

AgentCVR: Active Multi-Agent Cross-Video Reasoning via Script-Simulated Reinforcement Learning

Yilun Qiu, Jiahe Wang, Cilin Yan +4

Cross-Video Reasoning (CVR) has emerged as a critical frontier in multimodal intelligence, requiring models to retrieve, align, and aggregate evidence distributed across multiple v…

cs.CV2026

VideoSeeker: Incentivizing Instance-level Video Understanding via Native Agentic Tool Invocation

Yiming Zhao, Yu Zeng, Wenxuan Huang +11

Large Vision-Language Models (LVLMs) have shown significant progress in video understanding, yet they face substantial challenges in tasks requiring precise spatiotemporal localiza…

cs.CV2026

Weaver: End-to-End Agentic System Training for Video Interleaved Reasoning

Yudi Shi, Shangzhe Di, Qirui Chen +5

Video reasoning constitutes a comprehensive assessment of a model's capabilities, as it demands robust perceptual and interpretive skills, thereby serving as a means to explore the…

cs.CV2025

CrossVid: A Comprehensive Benchmark for Evaluating Cross-Video Reasoning in Multimodal Large Language Models

Jingyao Li, Jingyun Wang, Molin Tan +6

Cross-Video Reasoning (CVR) presents a significant challenge in video understanding, which requires simultaneous understanding of multiple videos to aggregate and compare informati…