5 citations · 9 across the 4 of their papers we have counts for
4 papers
LLaDA2.0-Uni: Unifying Multimodal Understanding and Generation with Diffusion Large Language Model
Inclusion AI, Tiwei Bie, Haoxing Chen +15
We present LLaDA2.0-Uni, a unified discrete diffusion large language model (dLLM) that supports multimodal understanding and generation within a natively integrated framework. Its…
VMT-Adapter: Parameter-Efficient Transfer Learning for Multi-Task Dense Scene Understanding
Yi Xin, Junlong Du, Qiang Wang +2
Large-scale pre-trained models have achieved remarkable success in various computer vision tasks. A standard approach to leverage these models is to fine-tune all model parameters…
MmAP : Multi-modal Alignment Prompt for Cross-domain Multi-task Learning
Yi Xin, Junlong Du, Qiang Wang +2
Multi-Task Learning (MTL) is designed to train multiple correlated tasks simultaneously, thereby enhancing the performance of individual tasks. Typically, a multi-task network stru…
SimpleMapping: Real-Time Visual-Inertial Dense Mapping with Deep Multi-View Stereo
Yingye Xin, Xingxing Zuo, Dongyue Lu +1
We present a real-time visual-inertial dense mapping method capable of performing incremental 3D mesh reconstruction with high quality using only sequential monocular images and in…