5 citations · 5 across the 2 of their papers we have counts for
4 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…
Rethinking Latent Visual Reasoning: Grounding Latent Reasoning in Visual Evidence
Xi Xiao, Tianchen Zhao, Youngeun Kim +10
Latent visual reasoning (LVR) enables multimodal large language models (MLLMs) to perform intermediate computation in continuous latent tokens rather than expressing every reasonin…
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…
Fraud Dataset Benchmark and Applications
Prince Grover, Julia Xu, Justin Tittelfitz +5
Standardized datasets and benchmarks have spurred innovations in computer vision, natural language processing, multi-modal and tabular settings. We note that, as compared to other…