2 papers
cs.CV2026
Fine-Grained Preference Optimization Improves Spatial Reasoning in VLMs
Yifan Shen, Yuanzhe Liu, Jingyuan Zhu +6
Current Vision-Language Models (VLMs) struggle with fine-grained spatial reasoning, particularly when multi-step logic and precise spatial alignment are required. In this work, we…
cs.CV2025
RzenEmbed: Towards Comprehensive Multimodal Retrieval
Weijian Jian, Yajun Zhang, Dawei Liang +4
The rapid advancement of Multimodal Large Language Models (MLLMs) has extended CLIP-based frameworks to produce powerful, universal embeddings for retrieval tasks. However, existin…