3 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…
cs.AI2026
Agentic Learner with Grow-and-Refine Multimodal Semantic Memory
Weihao Bo, Shan Zhang, Yanpeng Sun +9
MLLMs exhibit strong reasoning on isolated queries, yet they operate de novo -- solving each problem independently and often repeating the same mistakes. Existing memory-augmented…
cs.CL2026
ERNIE 5.0 Technical Report
Haifeng Wang, Hua Wu, Tian Wu +432
In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio…