3 papers
cs.CV2026
Cross-Modal Masked Compositional Concept Modeling for Enhancing Visio-Linguistic Compositionality
Wei Li, Zhen Huang, Xinmei Tian
Contrastively trained vision-language models like CLIP, have made remarkable progress in learning joint image-text representations, but still face challenges in compositional under…
cs.CV2026
Prefill-Time Intervention for Mitigating Hallucination in Large Vision-Language Models
Chengsheng Zhang, Chenghao Sun, Xinyan Jiang +2
Large Vision-Language Models (LVLMs) have achieved remarkable progress in visual-textual understanding, yet their reliability is critically undermined by hallucinations, i.e., the…
cs.LG2025
Leveraging Submodule Linearity Enhances Task Arithmetic Performance in LLMs
Rui Dai, Sile Hu, Xu Shen +3
Task arithmetic is a straightforward yet highly effective strategy for model merging, enabling the resultant model to exhibit multi-task capabilities. Recent research indicates tha…