6 citations · 7 across the 4 of their papers we have counts for
4 papers
Fast and Accurate Transferability Measurement by Evaluating Intra-class Feature Variance
Huiwen Xu, U Kang
Given a set of pre-trained models, how can we quickly and accurately find the most useful pre-trained model for a downstream task? Transferability measurement is to quantify how tr…
Accurate Retraining-free Pruning for Pretrained Encoder-based Language Models
Seungcheol Park, Hojun Choi, U Kang
Given a pretrained encoder-based language model, how can we accurately compress it without retraining? Retraining-free structured pruning algorithms are crucial in pretrained langu…
Accurate Bundle Matching and Generation via Multitask Learning with Partially Shared Parameters
Hyunsik Jeon, Jun-Gi Jang, Taehun Kim +1
How can we recommend existing bundles to users accurately? How can we generate new tailored bundles for users? Recommending a bundle, or a group of various items, has attracted wid…
Fast and Accurate Transferability Measurement for Heterogeneous Multivariate Data
Seungcheol Park, Huiwen Xu, Taehun Kim +3
Given a set of heterogeneous source datasets with their classifiers, how can we quickly find the most useful source dataset for a specific target task? We address the problem of me…