7 papers
Not All Tokens Matter Equally: Dynamic In-context Vector Distillation with Decisive-Token Supervision for Long-form Medical Report Generation
Ning Wu, Rui Liu, Xinkun Lin +5
Distilling demonstration effects into hidden-space interventions offers a lightweight alternative to full finetuning. However, existing multimodal variants are mostly evaluated on…
Growing a Multi-head Twig via Distillation and Reinforcement Learning to Accelerate Large Vision-Language Models
Zhenwei Shao, Mingyang Wang, Weijun Zhang +6
Large vision-language models (VLMs) have demonstrated remarkable capabilities in open-world multimodal understanding, yet their high computational overheads pose great challenges f…
MindGPT-4ov: An Enhanced MLLM via a Multi-Stage Post-Training Paradigm
Wei Chen, Chaoqun Du, Feng Gu +14
We present MindGPT-4ov, a multimodal large language model (MLLM) that introduces a general post-training paradigm spanning data production, model training, and efficient deployment…
MonkeyOCR v1.5 Technical Report: Unlocking Robust Document Parsing for Complex Patterns
Jiarui Zhang, Yuliang Liu, Zijun Wu +17
Document parsing is a core task in document intelligence, supporting applications such as information extraction, retrieval-augmented generation, and automated document analysis. H…
SRSplat: Feed-Forward Super-Resolution Gaussian Splatting from Sparse Multi-View Images
Xinyuan Hu, Changyue Shi, Chuxiao Yang +6
Feed-forward 3D reconstruction from sparse, low-resolution (LR) images is a crucial capability for real-world applications, such as autonomous driving and embodied AI. However, exi…
COPO: Consistency-Aware Policy Optimization
Jinghang Han, Jiawei Chen, Hang Shao +7
Reinforcement learning has significantly enhanced the reasoning capabilities of Large Language Models (LLMs) in complex problem-solving tasks. Recently, the introduction of DeepSee…