4 citations · 8 across the 37 of their papers we have counts for
6 papers · 1 filter
Content-aware Balanced Spectrum Encoding in Masked Modeling for Time Series Classification
Yudong Han, Haocong Wang, Yupeng Hu +3
Due to the superior ability of global dependency, transformer and its variants have become the primary choice in Masked Time-series Modeling (MTM) towards time-series classificatio…
Vision-guided and Mask-enhanced Adaptive Denoising for Prompt-based Image Editing
Kejie Wang, Xuemeng Song, Meng Liu +2
Text-to-image diffusion models have demonstrated remarkable progress in synthesizing high-quality images from text prompts, which boosts researches on prompt-based image editing th…
Token-level Correlation-guided Compression for Efficient Multimodal Document Understanding
Renshan Zhang, Yibo Lyu, Rui Shao +3
Cropping high-resolution document images into multiple sub-images is the most widely used approach for current Multimodal Large Language Models (MLLMs) to do document understanding…
MoME: Mixture of Multimodal Experts for Generalist Multimodal Large Language Models
Leyang Shen, Gongwei Chen, Rui Shao +2
Multimodal large language models (MLLMs) have demonstrated impressive capabilities across various vision-language tasks. However, a generalist MLLM typically underperforms compared…
MMGRec: Multimodal Generative Recommendation with Transformer Model
Han Liu, Yinwei Wei, Xuemeng Song +3
Multimodal recommendation aims to recommend user-preferred candidates based on her/his historically interacted items and associated multimodal information. Previous studies commonl…
Prompt-based Multi-interest Learning Method for Sequential Recommendation
Xue Dong, Xuemeng Song, Tongliang Liu +1
Multi-interest learning method for sequential recommendation aims to predict the next item according to user multi-faceted interests given the user historical interactions. Existin…