5 papers
InSight-doc: Agentic Visual Perception for Long-Document Understanding
Kaican Li, Weiyan Xie, Lewei Yao +4
Long-document understanding often requires reasoning over many visually rich pages, making inference costly and prone to context rot. In this work, we propose InSight-doc, an agent…
Causal Fine-Tuning under Latent Confounded Shift
Jialin Yu, Yuxiang Zhou, Haoxuan Li +6
Adapting to latent confounded shift remains a core challenge in modern AI. This setting is driven by hidden variables that induce spurious correlations between inputs and outputs d…
InSight-o3: Empowering Multimodal Foundation Models with Generalized Visual Search
Kaican Li, Lewei Yao, Jiannan Wu +7
The ability for AI agents to "think with images" requires a sophisticated blend of reasoning and perception. However, current open multimodal agents still largely fall short on the…
CannyEdit: Selective Canny Control and Dual-Prompt Guidance for Training-Free Image Editing
Weiyan Xie, Han Gao, Didan Deng +4
Recent advances in text-to-image (T2I) models have enabled training-free regional image editing by leveraging the generative priors of foundation models. However, existing methods…
Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models
Kaican Li, Weiyan Xie, Yongxiang Huang +5
Fine-tuning foundation models often compromises their robustness to distribution shifts. To remedy this, most robust fine-tuning methods aim to preserve the pre-trained features. H…