10 papers
Mitigating Factual Hallucination in Large Reasoning Models via Mixed-Mode Advantage Regularization
Kaishen Wang, Tong Zheng, Xuehao Cui +3
Large reasoning models (LRMs) improve language model capabilities by generating explicit thinking traces before final answers. In factuality-oriented question answering (QA), such…
Enhancing Oracle Bone Inscription Recognition via Multi-Scale Layer Attention
Chaowen Yan, Kaishen Wang, Yong Wang +2
Oracle Bone Inscriptions (OBIs) recognition plays a crucial role in understanding ancient Chinese culture. However, accurately recognizing OBIs remains highly challenging due to th…
Unsafe by Reciprocity: How Generation-Understanding Coupling Undermines Safety in Unified Multimodal Models
Kaishen Wang, Heng Huang
Recent advances in Large Language Models (LLMs) and Text-to-Image (T2I) models have led to the emergence of Unified Multimodal Models (UMMs), where multimodal understanding and ima…
ImAgent: A Unified Multimodal Agent Framework for Test-Time Scalable Image Generation
Kaishen Wang, Ruibo Chen, Tong Zheng +1
Recent text-to-image (T2I) models have made remarkable progress in generating visually realistic and semantically coherent images. However, they still suffer from randomness and in…
Multi-Crit: Benchmarking Multimodal Judges on Pluralistic Criteria-Following
Tianyi Xiong, Yi Ge, Ming Li +13
Large multimodal models (LMMs) are increasingly adopted as judges in multimodal evaluation systems due to their strong instruction following and consistency with human preferences.…
Enhancing Feature Fusion of U-like Networks with Dynamic Skip Connections
Yue Cao, Quansong He, Kaishen Wang +3
U-like networks have become fundamental frameworks in medical image segmentation through skip connections that bridge high-level semantics and low-level spatial details. Despite th…