5 papers · 1 filter
Counteracting Matthew Effect in Self-Improvement of LVLMs through Head-Tail Re-balancing
Xin Guo, Zhiheng Xi, Yiwen Ding +6
Self-improvement has emerged as a mainstream paradigm for advancing the reasoning capabilities of large vision-language models (LVLMs), where models explore and learn from successf…
Unlocking the Essence of Beauty: Advanced Aesthetic Reasoning with Relative-Absolute Policy Optimization
Boyang Liu, Yifan Hu, Senjie Jin +5
Multimodal large language models (MLLMs) are well suited to image aesthetic assessment, as they can capture high-level aesthetic features leveraging their cross-modal understanding…
SPA-VL: A Comprehensive Safety Preference Alignment Dataset for Vision Language Model
Yongting Zhang, Lu Chen, Guodong Zheng +10
The emergence of Vision Language Models (VLMs) has brought unprecedented advances in understanding multimodal information. The combination of textual and visual semantics in VLMs i…
Mitigating Object Hallucinations in MLLMs via Multi-Frequency Perturbations
Shuo Li, Jiajun Sun, Guodong Zheng +10
Recently, multimodal large language models (MLLMs) have demonstrated remarkable performance in visual-language tasks. However, the authenticity of the responses generated by MLLMs…
Have the VLMs Lost Confidence? A Study of Sycophancy in VLMs
Shuo Li, Tao Ji, Xiaoran Fan +10
In the study of LLMs, sycophancy represents a prevalent hallucination that poses significant challenges to these models. Specifically, LLMs often fail to adhere to original correct…