conftrace_

label efficiency

31 papers

Explore in graph

Co-occurring keywords

active learning (1301) online learning (1777) regret bound (1926) query strategy (38) large language model (13587) domain adaptation (4595) transfer learning (5449) semi-supervised learning (2341) synthetic datum (765) data selection (221)

Papers

Heavy Labels Out! Dataset Distillation with Label Space Lightening ICCV 2025
MythTriage: Scalable Detection of Opioid Use Disorder Myths on a Video-Sharing Platform EMNLP 2025
Benchmarking Debiasing Methods for LLM-based Parameter Estimates EMNLP 2025
Contextual Active Model Selection NIPS 2024
Class Balancing for Efficient Active Learning in Imbalanced Datasets EACL 2024
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models ACL 2024
Re-Thinking Federated Active Learning Based on Inter-Class Diversity CVPR 2023
Entity Disambiguation on a Tight Labeling Budget EMNLP 2023
Reducing Annotation Effort by Identifying and Labeling Contextually Diverse Classes for Semantic Segmentation Under Domain Shift WACV 2023
Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels ICCV 2023
Unsupervised Active Learning: Optimizing Labeling Cost-Effectiveness for Automatic Speech Recognition INTERSPEECH 2023
Actively Testing Your Model While It Learns: Realizing Label-Efficient Learning in Practice NIPS 2023
LanSER: Language-Model Supported Speech Emotion Recognition INTERSPEECH 2023
Adaptive Selective Sampling for Online Prediction with Experts NIPS 2023
A label efficient two-sample test UAI 2022
Metric-Fair Active Learning ICML 2022
Not All Labels Are Equal: Rationalizing the Labeling Costs for Training Object Detection CVPR 2022
Exponential savings in agnostic active learning through abstention COLT 2021
Meta-LMTC: Meta-Learning for Large-Scale Multi-Label Text Classification EMNLP 2021
A Comparative Survey: Benchmarking for Pool-based Active Learning IJCAI 2021
Reliable Estimates of Interpretable Cue Effects with Active Learning in Psycholinguistic Research INTERSPEECH 2021
What if We Only Use Real Datasets for Scene Text Recognition? Toward Scene Text Recognition With Fewer Labels CVPR 2021
Bayesian Active Learning by Soft Mean Objective Cost of Uncertainty AISTATS 2021
Self-Paced Active Learning: Query the Right Thing at the Right Time AAAI 2019
Marginal Singularity, and the Benefits of Labels in Covariate-Shift COLT 2018