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
'5
'10
'15
'20
'25
Papers (including subtopics)
On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability
NeurIPS 2024
On Parameter Estimation in Deviated Gaussian Mixture of Experts
AISTATS 2024
On Representation Complexity of Model-based and Model-free Reinforcement Learning
ICLR 2024
On Scaling Up a Multilingual Vision and Language Model
CVPR 2024
On Sensitivity of Learning with Limited Labelled Data to the Effects of Randomness: Impact of Interactions and Systematic Choices
EMNLP 2024
On Softmax Direct Preference Optimization for Recommendation
NeurIPS 2024
On task-relevant loss functions in meta-reinforcement learning
L4DC 2024
On the Actionability of Outcome Prediction
AAAI 2024
On the Adversarial Robustness of Benjamini Hochberg
NeurIPS 2024
On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift
NeurIPS 2024
On the Comparison between Multi-modal and Single-modal Contrastive Learning
NeurIPS 2024
On the Complexity of Teaching a Family of Linear Behavior Cloning Learners
NeurIPS 2024
On the Computability of Robust PAC Learning
COLT 2024
On the Computational Complexity of Private High-dimensional Model Selection
NeurIPS 2024
On the Computational Landscape of Replicable Learning
NeurIPS 2024
On the connection between Noise-Contrastive Estimation and Contrastive Divergence
AISTATS 2024
On the Content Bias in Frechet Video Distance
CVPR 2024
On the Convergence of an Adaptive Momentum Method for Adversarial Attacks
AAAI 2024
On the Convergence of Loss and Uncertainty-based Active Learning Algorithms
NeurIPS 2024
On the Distance from Calibration in Sequential Prediction
COLT 2024
On the Diversity and Realism of Distilled Dataset: An Efficient Dataset Distillation Paradigm
CVPR 2024
On the Duality Between Sharpness-Aware Minimization and Adversarial Training
ICML 2024
On the Effectiveness of Adversarial Robustness for Abuse Mitigation with Counterspeech
NAACL 2024
On the Effect of Batch Size in Byzantine-Robust Distributed Learning
ICLR 2024
On the Effects of Data Scale on UI Control Agents
NeurIPS 2024