4 papers
Hidden Decoding at Scale: Latent Computation Scaling for Large Language Models
Aiwei Liu, Cheng Shi, Chuhan Wu +44
Scaling Large Language Models (LLMs) has been driven mainly by enlarging the Transformer backbone, but for an already-strong model this requires another round of costly pretraining…
POINTS-Long: Adaptive Dual-Mode Visual Reasoning in MLLMs
Haicheng Wang, Yuan Liu, Yikun Liu +9
Multimodal Large Language Models (MLLMs) have recently demonstrated remarkable capabilities in cross-modal understanding and generation. However, the rapid growth of visual token s…
POINTS-GUI-G: GUI-Grounding Journey
Zhongyin Zhao, Yuan Liu, Yikun Liu +7
The rapid advancement of vision-language models has catalyzed the emergence of GUI agents, which hold immense potential for automating complex tasks, from online shopping to flight…
POINTS-Reader: Distillation-Free Adaptation of Vision-Language Models for Document Conversion
Yuan Liu, Zhongyin Zhao, Le Tian +8
High-quality labeled data is essential for training accurate document conversion models, particularly in domains with complex formats such as tables, formulas, and multi-column tex…