167 citations · 914 across the 103 of their papers we have counts for
19 papers · 1 filter
Channel Merging: Preserving Specialization for Merged Experts
Mingyang Zhang, Jing Liu, Ganggui Ding +3
Lately, the practice of utilizing task-specific fine-tuning has been implemented to improve the performance of large language models (LLM) in subsequent tasks. Through the integrat…
Enhancing Perception Capabilities of Multimodal LLMs with Training-Free Fusion
Zhuokun Chen, Jinwu Hu, Zeshuai Deng +3
Multimodal LLMs (MLLMs) equip language models with visual capabilities by aligning vision encoders with language models. Existing methods to enhance the visual perception of MLLMs…
ZipAR: Parallel Auto-regressive Image Generation through Spatial Locality
Yefei He, Feng Chen, Yuanyu He +4
In this paper, we propose ZipAR, a training-free, plug-and-play parallel decoding framework for accelerating auto-regressive (AR) visual generation. The motivation stems from the o…
MVSplat360: Feed-Forward 360 Scene Synthesis from Sparse Views
Yuedong Chen, Chuanxia Zheng, Haofei Xu +4
We introduce MVSplat360, a feed-forward approach for 360° novel view synthesis (NVS) of diverse real-world scenes, using only sparse observations. This setting is inherently ill-po…
Evaluating and Advancing Multimodal Large Language Models in Perception Ability Lens
Feng Chen, Chenhui Gou, Jing Liu +6
As multimodal large language models (MLLMs) advance rapidly, rigorous evaluation has become essential, providing further guidance for their development. In this work, we focus on a…
ZipVL: Efficient Large Vision-Language Models with Dynamic Token Sparsification
Yefei He, Feng Chen, Jing Liu +4
The efficiency of large vision-language models (LVLMs) is constrained by the computational bottleneck of the attention mechanism during the prefill phase and the memory bottleneck…
McCaD: Multi-Contrast MRI Conditioned, Adaptive Adversarial Diffusion Model for High-Fidelity MRI Synthesis
Sanuwani Dayarathna, Kh Tohidul Islam, Bohan Zhuang +4
Magnetic Resonance Imaging (MRI) is instrumental in clinical diagnosis, offering diverse contrasts that provide comprehensive diagnostic information. However, acquiring multiple MR…
GMAI-MMBench: A Comprehensive Multimodal Evaluation Benchmark Towards General Medical AI
Pengcheng Chen, Jin Ye, Guoan Wang +15
Large Vision-Language Models (LVLMs) are capable of handling diverse data types such as imaging, text, and physiological signals, and can be applied in various fields. In the medic…
InfiniMotion: Mamba Boosts Memory in Transformer for Arbitrary Long Motion Generation
Zeyu Zhang, Akide Liu, Qi Chen +5
Text-to-motion generation holds potential for film, gaming, and robotics, yet current methods often prioritize short motion generation, making it challenging to produce long motion…
SAM-Med3D-MoE: Towards a Non-Forgetting Segment Anything Model via Mixture of Experts for 3D Medical Image Segmentation
Guoan Wang, Jin Ye, Junlong Cheng +5
Volumetric medical image segmentation is pivotal in enhancing disease diagnosis, treatment planning, and advancing medical research. While existing volumetric foundation models for…
ME-Switch: A Memory-Efficient Expert Switching Framework for Large Language Models
Jing Liu, Ruihao Gong, Mingyang Zhang +3
LLM development involves pre-training a foundation model on massive data, followed by fine-tuning on task-specific data to create specialized experts. Serving these experts can pos…
Streaming Video Diffusion: Online Video Editing with Diffusion Models
Feng Chen, Zhen Yang, Bohan Zhuang +1
We present a novel task called online video editing, which is designed to edit \textbf{streaming} frames while maintaining temporal consistency. Unlike existing offline video editi…
ZipCache: Accurate and Efficient KV Cache Quantization with Salient Token Identification
Yefei He, Luoming Zhang, Weijia Wu +3
KV cache stores key and value states from previous tokens to avoid re-computation, yet it demands substantial storage space, especially for long sequences. Adaptive KV cache compre…
MiniCache: KV Cache Compression in Depth Dimension for Large Language Models
Akide Liu, Jing Liu, Zizheng Pan +3
A critical approach for efficiently deploying computationally demanding large language models (LLMs) is Key-Value (KV) caching. The KV cache stores key-value states of previously g…
LongVLM: Efficient Long Video Understanding via Large Language Models
Yuetian Weng, Mingfei Han, Haoyu He +2
Empowered by Large Language Models (LLMs), recent advancements in Video-based LLMs (VideoLLMs) have driven progress in various video understanding tasks. These models encode video…
MVSplat: Efficient 3D Gaussian Splatting from Sparse Multi-View Images
Yuedong Chen, Haofei Xu, Chuanxia Zheng +5
We introduce MVSplat, an efficient model that, given sparse multi-view images as input, predicts clean feed-forward 3D Gaussians. To accurately localize the Gaussian centers, we bu…
Motion Mamba: Efficient and Long Sequence Motion Generation
Zeyu Zhang, Akide Liu, Ian Reid +3
Human motion generation stands as a significant pursuit in generative computer vision, while achieving long-sequence and efficient motion generation remains challenging. Recent adv…
T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching
Zizheng Pan, Bohan Zhuang, De-An Huang +5
Sampling from diffusion probabilistic models (DPMs) is often expensive for high-quality image generation and typically requires many steps with a large model. In this paper, we int…
ModaVerse: Efficiently Transforming Modalities with LLMs
Xinyu Wang, Bohan Zhuang, Qi Wu
Humans possess the capability to comprehend diverse modalities and seamlessly transfer information between them. In this work, we introduce ModaVerse, a Multi-modal Large Language…