20 citations · 37 across the 6 of their papers we have counts for
17 papers
Multisize Dataset Condensation
Yang He, Lingao Xiao, Joey Tianyi Zhou +1
While dataset condensation effectively enhances training efficiency, its application in on-device scenarios brings unique challenges. 1) Due to the fluctuating computational resour…
Shortcuts Arising from Contrast: Effective and Covert Clean-Label Attacks in Prompt-Based Learning
Xiaopeng Xie, Ming Yan, Xiwen Zhou +4
Prompt-based learning paradigm has demonstrated remarkable efficacy in enhancing the adaptability of pretrained language models (PLMs), particularly in few-shot scenarios. However,…
CrossGLG: LLM Guides One-shot Skeleton-based 3D Action Recognition in a Cross-level Manner
Tingbing Yan, Wenzheng Zeng, Yang Xiao +5
Most existing one-shot skeleton-based action recognition focuses on raw low-level information (e.g., joint location), and may suffer from local information loss and low generalizat…
Direct Distillation between Different Domains
Jialiang Tang, Shuo Chen, Gang Niu +4
Knowledge Distillation (KD) aims to learn a compact student network using knowledge from a large pre-trained teacher network, where both networks are trained on data from the same…
A Concise but High-performing Network for Image Guided Depth Completion in Autonomous Driving
Moyun Liu, Bing Chen, Youping Chen +4
Depth completion is a crucial task in autonomous driving, aiming to convert a sparse depth map into a dense depth prediction. Due to its potentially rich semantic information, RGB…
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data
Zikai Xiao, Zihan Chen, Liyinglan Liu +6
Federated Long-Tailed Learning (Fed-LT), a paradigm wherein data collected from decentralized local clients manifests a globally prevalent long-tailed distribution, has garnered co…