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cs.CV2025
Helping CLIP See Both the Forest and the Trees: A Decomposition and Description Approach
Leyan Xue, Zongbo Han, Guangyu Wang +3
Vision-Language Models (VLMs) like CLIP achieve cross-modal semantic alignment through contrastive learning, exhibiting robust zero-shot generalization. Traditional prompt engineer…
cs.CL2025
Computational Reasoning of Large Language Models
Haitao Wu, Zongbo Han, Joey Tianyi Zhou +2
With the rapid development and widespread application of Large Language Models (LLMs), multidimensional evaluation has become increasingly critical. However, current evaluations ar…
cs.CV2025
MedSG-Bench: A Benchmark for Medical Image Sequences Grounding
Jingkun Yue, Siqi Zhang, Zinan Jia +4
Visual grounding is essential for precise perception and reasoning in multimodal large language models (MLLMs), especially in medical imaging domains. While existing medical visual…