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Methodology
← Learning Types
Machine Learning
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Learning Types
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Active Learning
1885 directly classified papers
Papers per year
2001: 1
2002: 1
2004: 2
2005: 4
2006: 8
2007: 12
2008: 8
2009: 11
2010: 20
2011: 26
2012: 38
2013: 50
2014: 46
2015: 39
2016: 45
2017: 76
2018: 102
2019: 160
2020: 152
2021: 232
2022: 215
2023: 252
2024: 222
2025: 119
2026: 44
Papers
Learning the Pareto Set Under Incomplete Preferences: Pure Exploration in Vector Bandits
AISTATS 2024
Learnability Matters: Active Learning for Video Captioning
NIPS 2024
D3GU: Multi-Target Active Domain Adaptation via Enhancing Domain Alignment
WACV 2024
Practice Makes Perfect: Planning to Learning Skill Parameter Policies
RSS 2024
Monocular 3D Object Detection With LiDAR Guided Semi Supervised Active Learning
WACV 2024
A Greedy Approximation for k-Determinantal Point Processes
AISTATS 2024
Boundary Matters: A Bi-Level Active Finetuning Method
NIPS 2024
Active preference learning for ordering items in- and out-of-sample
NIPS 2024
Harnessing the Power of Beta Scoring in Deep Active Learning for Multi-Label Text Classification
AAAI 2024
Active learning of neural population dynamics using two-photon holographic optogenetics
NIPS 2024
Agnostic Active Learning of Single Index Models with Linear Sample Complexity
COLT 2024
Adaptive importance sampling for heavy-tailed distributions via $α$-divergence minimization
AISTATS 2024
Evolving Knowledge Distillation with Large Language Models and Active Learning
COLING 2024
Asking More Informative Questions for Grounded Retrieval
NAACL 2024
Semi-supervised Active Learning for Video Action Detection
AAAI 2024
Efficiently Acquiring Human Feedback with Bayesian Deep Learning
EACL 2024
Active Learning with LLMs for Partially Observed and Cost-Aware Scenarios
NIPS 2024
Enhancing Semi-supervised Domain Adaptation via Effective Target Labeling
AAAI 2024
Active Prompting with Chain-of-Thought for Large Language Models
ACL 2024
Enhancing Text Classification through LLM-Driven Active Learning and Human Annotation
EACL 2024
Linear Uncertainty Quantification of Graphical Model Inference
NIPS 2024
Optimizing Relation Extraction in Medical Texts through Active Learning: A Comparative Analysis of Trade-offs
EACL 2024
CoLAL: Co-learning Active Learning for Text Classification
AAAI 2024
Using Large Language Models to Improve Query-based Constraint Acquisition
IJCAI 2024
Reciprocal Learning
NIPS 2024
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