3 papers
cs.CV2026
Cheers: Decoupling Patch Details from Semantic Representations Enables Unified Multimodal Comprehension and Generation
Yichen Zhang, Da Peng, Zonghao Guo +19
A recent cutting-edge topic in multimodal modeling is to unify visual comprehension and generation within a single model. However, the two tasks demand mismatched decoding regimes…
cs.CV2025
GeoViS: Geospatially Rewarded Visual Search for Remote Sensing Visual Grounding
Peirong Zhang, Yidan Zhang, Luxiao Xu +6
Recent advances in multimodal large language models(MLLMs) have led to remarkable progress in visual grounding, enabling fine-grained cross-modal alignment between textual queries…
cs.CV2025
ProCLIP: Progressive Vision-Language Alignment via LLM-based Embedder
Xiaoxing Hu, Kaicheng Yang, Ziyang Gong +6
The original CLIP text encoder is limited by a maximum input length of 77 tokens, which hampers its ability to effectively process long texts and perform fine-grained semantic unde…