2 papers
cs.CV2026
P-MTP: Efficient Document Parsing via Multi-Token Prediction with Progressive Depth Scaling
Le Xiang, Chenxi Zhai, Shu Wei +5
Vision-Language Models (VLMs) have revolutionized document parsing by enabling end-to-end mapping from images to structured text, imposing a significant latency bottleneck, particu…
stat.ML2026
AURA: Adaptive Uncertainty-aware Refinement for LLM-as-a-Judge Auditing
Zilong Zhang, Yi-Ting Hung, Weiyi He +3
Large language models (LLMs) are increasingly used as judges for open-ended generation, as large-scale human evaluation is often expensive and difficult to scale, yet their prefere…