285 citations · 333 across the 13 of their papers we have counts for
6 papers · 1 filter
Awaker2.5-VL: Stably Scaling MLLMs with Parameter-Efficient Mixture of Experts
Jinqiang Long, Yanqi Dai, Guoxing Yang +4
As the research of Multimodal Large Language Models (MLLMs) becomes popular, an advancing MLLM model is typically required to handle various textual and visual tasks (e.g., VQA, De…
VDT: General-purpose Video Diffusion Transformers via Mask Modeling
Haoyu Lu, Guoxing Yang, Nanyi Fei +4
This work introduces Video Diffusion Transformer (VDT), which pioneers the use of transformers in diffusion-based video generation. It features transformer blocks with modularized…
LGDN: Language-Guided Denoising Network for Video-Language Modeling
Haoyu Lu, Mingyu Ding, Nanyi Fei +2
Video-language modeling has attracted much attention with the rapid growth of web videos. Most existing methods assume that the video frames and text description are semantically c…
COTS: Collaborative Two-Stream Vision-Language Pre-Training Model for Cross-Modal Retrieval
Haoyu Lu, Nanyi Fei, Yuqi Huo +3
Large-scale single-stream pre-training has shown dramatic performance in image-text retrieval. Regrettably, it faces low inference efficiency due to heavy attention layers. Recentl…
Contrastive Prototype Learning with Augmented Embeddings for Few-Shot Learning
Yizhao Gao, Nanyi Fei, Guangzhen Liu +3
Most recent few-shot learning (FSL) methods are based on meta-learning with episodic training. In each meta-training episode, a discriminative feature embedding and/or classifier a…
Zero-Shot Learning with Sparse Attribute Propagation
Nanyi Fei, Jiechao Guan, Zhiwu Lu +2
Zero-shot learning (ZSL) aims to recognize a set of unseen classes without any training images. The standard approach to ZSL requires a set of training images annotated with seen c…