Learning Types
56,253 papers (3 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Self-Supervised Learning (8,965)
Adversarial Learning (5,204)
Unsupervised Learning (4,874)
Transfer Learning (4,808)
Weakly Supervised Learning (3,938)
Contrastive Learning (3,748)
Zero-Shot Learning (3,130)
Semi-Supervised Learning (3,128)
Reinforcement Learning (3,118)
Multi-Task Learning (2,556)
Evaluation (2,164)
Continual Learning (2,107)
Active Learning (1,983)
Few-Shot Learning (1,840)
Deep Learning (1,404)
Online Learning (1,360)
Multi-Armed Bandits (1,327)
Multimodal Learning (1,289)
Supervised Learning (986)
Multi-Agent Systems (813)
Uncertainty Quantification (805)
Causal Inference (636)
Robustness (576)
Retrieval-Augmented Generation (565)
Fine-Tuning (490)
Ensemble Learning (482)
In-Context Learning (439)
Multi-Label Classification (430)
Imitation Learning (387)
Prompt Engineering (270)
Multi-Lingual Learning (269)
Distribution Shift (264)
Reinforcement Learning from Human Feedback (209)
Regularization (207)
Exploration-Exploitation (203)
Generative Models (200)
Multi-Objective Optimization (185)
Out-of-Distribution Detection (176)
Sparse Learning (165)
Sampling (150)
Preference Learning (136)
Offline Reinforcement Learning (130)
Multi-Label Learning (128)
Markov Decision Process (127)
Neural Architecture Search (122)
Multi-Instance Learning (121)
Multi-View Learning (117)
Robust Learning (110)
Generative Model (110)
Time Series (108)
Large Language Models (104)
Exploration (103)
Hyperparameter Optimization (99)
Machine Unlearning (95)
Imbalanced Learning (93)
Machine Translation (93)
Multi-Class Classification (85)
Differential Privacy (82)
Time Series Analysis (71)
Reasoning (70)
Calibration (67)
Structure Learning (66)
Physics-Informed Learning (62)
Class Imbalance (58)
Model-Based RL (55)
Interactive Learning (55)
Multi-Domain Learning (47)
Inverse Reinforcement Learning (46)
Crowdsourcing (40)
Off-Policy Learning (38)
Label Noise (38)
Noisy Label Learning (35)
Offline RL (32)
Attention (32)
Evolutionary Algorithm (32)
Decision Making (31)
Policy Learning (30)
Personalization (28)
Low-Resource Learning (26)
Collaborative Filtering (25)
Self-Training (24)
Sequential Modeling (24)
Parameter Estimation (23)
Survival Analysis (21)
Machine Learning (20)
Parameter-Efficient Fine-Tuning (20)
Synthetic Data Generation (20)
Annotation (18)
Symbolic Regression (18)
AutoML (16)
Security (15)
Multi-Source Learning (13)
Distant Supervision (13)
Text Generation (11)
Distributional Reinforcement Learning (9)
Sentiment Analysis (9)
Multi-Hop Reasoning (9)
Language Modeling (9)
Code Generation (8)
Multi-Object Tracking (8)
Natural Language Inference (7)
Chain-of-Thought (6)
Question Answering (5)
Papers per year
1
8
12
26
18
20
135
136
147
149
220
231
316
526
460
477
660
1,314
2,083
3,689
4,652
5,914
6,826
8,201
8,755
9,258
2,019
2000
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'15
'20
'25
Papers (including subtopics)
Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification
AAAI 2024
ARC: A Generalist Graph Anomaly Detector with In-Context Learning
NeurIPS 2024
ArcAid: Analysis of Archaeological Artifacts Using Drawings
WACV 2024
ArchLock: Locking DNN Transferability at the Architecture Level with a Zero-Cost Binary Predictor
ICLR 2024
Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantification
NeurIPS 2024
Are AI-Generated Text Detectors Robust to Adversarial Perturbations?
ACL 2024
A Recipe for Improved Certifiable Robustness
ICLR 2024
A Recipe for Scaling up Text-to-Video Generation with Text-free Videos
CVPR 2024
Are Data Augmentation Methods in Named Entity Recognition Applicable for Uncertainty Estimation?
EMNLP 2024
Are Emergent Abilities in Large Language Models just In-Context Learning?
ACL 2024
Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks?
NeurIPS 2024
Are Human-generated Demonstrations Necessary for In-context Learning?
ICLR 2024
A Reinforcement-Learning-Based Multiple-Column Selection Strategy for Column Generation
AAAI 2024
Are Language Models Actually Useful for Time Series Forecasting?
NeurIPS 2024
Are Large Language Models Consistent over Value-laden Questions?
EMNLP 2024
Are Large Language Models Good Statisticians?
NeurIPS 2024
Are Large Language Models (LLMs) Good Social Predictors?
EMNLP 2024
Are Large Language Models State-of-the-art Quality Estimators for Machine Translation of User-generated Content?
EMNLP 2024
Are LLMs Capable of Data-based Statistical and Causal Reasoning? Benchmarking Advanced Quantitative Reasoning with Data
ACL 2024
Are LLMs Good Zero-Shot Fallacy Classifiers?
EMNLP 2024
Are Machines Better at Complex Reasoning? Unveiling Human-Machine Inference Gaps in Entailment Verification
ACL 2024
Are modern neural ASR architectures robust for polysynthetic languages?
EMNLP 2024
Are More LLM Calls All You Need? Towards the Scaling Properties of Compound AI Systems
NeurIPS 2024
Are Natural Domain Foundation Models Useful for Medical Image Classification?
WACV 2024
Are Recent Deep Learning-Based Speech Enhancement Methods Ready to Confront Real-World Noisy Environments?
Interspeech 2024