8 papers · 1 filter
Enhancing Video Physical Consistency via Role-aware Joint Training and Modality-decoupled Denoising
Guangting Zheng, Haojing Chen, Hao Li +6
While modern video diffusion models excel in visual fidelity, maintaining long-range physical consistency remains a formidable challenge. Conventional pixel-reconstruction objectiv…
SWIFT: Prompt-Adaptive Memory for Efficient Interactive Long Video Generation
Shanwen Tan, Hao Li, Jingtao Zhang +4
Streaming long-video generation faces a central challenge in continuous semantic switching, requiring adaptive memory to preserve coherent visual evolution. Current approaches rely…
Mono-InternVL-1.5: Towards Cheaper and Faster Monolithic Multimodal Large Language Models
Gen Luo, Wenhan Dou, Wenhao Li +9
This paper focuses on monolithic Multimodal Large Language Models (MLLMs), which integrate visual encoding and language decoding into a single model. Existing structures and pre-tr…
Mono-InternVL: Pushing the Boundaries of Monolithic Multimodal Large Language Models with Endogenous Visual Pre-training
Gen Luo, Xue Yang, Wenhan Dou +5
In this paper, we focus on monolithic Multimodal Large Language Models (MLLMs) that integrate visual encoding and language decoding into a single LLM. In particular, we identify th…
Maintaining Structural Integrity in Parameter Spaces for Parameter Efficient Fine-tuning
Chongjie Si, Xuehui Wang, Xue Yang +6
Adapting pre-trained foundation models for various downstream tasks has been prevalent in artificial intelligence. Due to the vast number of tasks and high costs, adjusting all par…
A Simple Aerial Detection Baseline of Multimodal Language Models
Qingyun Li, Yushi Chen, Xinya Shu +4
The multimodal language models (MLMs) based on generative pre-trained Transformer are considered powerful candidates for unifying various domains and tasks. MLMs developed for remo…