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cs.CV2026
WinARDet: Compressed Window Auto-Regression for Long-Horizon Vision-Language Grounding
Chenxu Wang, Hangyi Kuang, Bo-Wen Yin +6
MLLM-based detectors formulate vision-language grounding as autoregressive coordinate generation, yet in dense scenes, they often collapse into a box repetition loop, repeatedly em…
cs.CV2026
CrystaL: Spontaneous Emergence of Visual Latents in MLLMs
Yang Zhang, Danyang Li, Yuxuan Li +4
Multimodal Large Language Models (MLLMs) have achieved remarkable performance by integrating powerful language backbones with large-scale visual encoders. Among these, latent Chain…
eess.IV2026
Q-Probe: Scaling Image Quality Assessment to High Resolution via Context-Aware Agentic Probing
Xiang Li, Xueheng Li, Yu Wang +4
Reinforcement Learning (RL) has empowered Multimodal Large Language Models (MLLMs) to achieve superior human preference alignment in Image Quality Assessment (IQA). However, existi…