1 citations · 1 across the 4 of their papers we have counts for
5 papers
ALoDLM: Adaptively Looped Diffusion Language Models
Liancheng Fang, Zhuowei Li, Youngeun Kim +10
Diffusion language models (DLMs) enable fast generation by predicting multiple tokens in parallel, but their practical adoption remains limited by a persistent quality gap relative…
VisRef: Visual Refocusing while Thinking Improves Test-Time Scaling in Multi-Modal Large Reasoning Models
Soumya Suvra Ghosal, Youngeun Kim, Zhuowei Li +6
Advances in large reasoning models have shown strong performance on complex reasoning tasks by scaling test-time compute through extended reasoning. However, recent studies observe…
Ground-V: Teaching VLMs to Ground Complex Instructions in Pixels
Yongshuo Zong, Qin Zhang, Dongsheng An +6
This work presents a simple yet effective workflow for automatically scaling instruction-following data to elicit pixel-level grounding capabilities of VLMs under complex instructi…
D3GU: Multi-Target Active Domain Adaptation via Enhancing Domain Alignment
Lin Zhang, Linghan Xu, Saman Motamed +2
Unsupervised domain adaptation (UDA) for image classification has made remarkable progress in transferring classification knowledge from a labeled source domain to an unlabeled tar…
Threshold-Consistent Margin Loss for Open-World Deep Metric Learning
Qin Zhang, Linghan Xu, Qingming Tang +4
Existing losses used in deep metric learning (DML) for image retrieval often lead to highly non-uniform intra-class and inter-class representation structures across test classes an…