787 citations · 2.9k across the 66 of their papers we have counts for
68 papers
Prompt Tuning for Generative Multimodal Pretrained Models
Hao Yang, Junyang Lin, An Yang +3
Prompt tuning has become a new paradigm for model tuning and it has demonstrated success in natural language pretraining and even vision pretraining. In this work, we explore the t…
Single Stage Virtual Try-on via Deformable Attention Flows
Shuai Bai, Huiling Zhou, Zhikang Li +2
Virtual try-on aims to generate a photo-realistic fitting result given an in-shop garment and a reference person image. Existing methods usually build up multi-stage frameworks to…
Knowledge Distillation of Transformer-based Language Models Revisited
Chengqiang Lu, Jianwei Zhang, Yunfei Chu +5
In the past few years, transformer-based pre-trained language models have achieved astounding success in both industry and academia. However, the large model size and high run-time…
Device-Cloud Collaborative Recommendation via Meta Controller
Jiangchao Yao, Feng Wang, Xichen Ding +4
On-device machine learning enables the lightweight deployment of recommendation models in local clients, which reduces the burden of the cloud-based recommenders and simultaneously…
Instance-wise Prompt Tuning for Pretrained Language Models
Yuezihan Jiang, Hao Yang, Junyang Lin +6
Prompt Learning has recently gained great popularity in bridging the gap between pretraining tasks and various downstream tasks. It freezes Pretrained Language Models (PLMs) and on…
M6-Fashion: High-Fidelity Multi-modal Image Generation and Editing
Zhikang Li, Huiling Zhou, Shuai Bai +3
The fashion industry has diverse applications in multi-modal image generation and editing. It aims to create a desired high-fidelity image with the multi-modal conditional signal a…