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)
BertRLFuzzer: A BERT and Reinforcement Learning Based Fuzzer (Student Abstract)
AAAI 2024
Best Arm Identification with Resource Constraints
AISTATS 2024
Best-of-Both-Worlds Algorithms for Linear Contextual Bandits
AISTATS 2024
Better Batch for Deep Probabilistic Time Series Forecasting
AISTATS 2024
BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practices
NeurIPS 2024
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective
AISTATS 2024
Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks
ICML 2024
Better than Random: Reliable NLG Human Evaluation with Constrained Active Sampling
AAAI 2024
BetterV: Controlled Verilog Generation with Discriminative Guidance
ICML 2024
BEV-MAE: Bird’s Eye View Masked Autoencoders for Point Cloud Pre-training in Autonomous Driving Scenarios
AAAI 2024
Beware of Road Markings: A New Adversarial Patch Attack to Monocular Depth Estimation
NeurIPS 2024
Beyond Accuracy: Ensuring Correct Predictions With Correct Rationales
NeurIPS 2024
Beyond Active Learning: Leveraging the Full Potential of Human Interaction via Auto-Labeling, Human Correction, and Human Verification
WACV 2024
Beyond Catoni: Sharper Rates for Heavy-Tailed and Robust Mean Estimation
COLT 2024
Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable?
NeurIPS 2024
Beyond Correlation: Interpretable Evaluation of Machine Translation Metrics
EMNLP 2024
Beyond Document Page Classification: Design, Datasets, and Challenges
WACV 2024
Beyond Entities: A Large-Scale Multi-Modal Knowledge Graph with Triplet Fact Grounding
AAAI 2024
Beyond Euclidean: Dual-Space Representation Learning for Weakly Supervised Video Violence Detection
NeurIPS 2024
Beyond Expected Return: Accounting for Policy Reproducibility When Evaluating Reinforcement Learning Algorithms
AAAI 2024
Beyond First-Order Tweedie: Solving Inverse Problems using Latent Diffusion
CVPR 2024
Beyond Grounding: Extracting Fine-Grained Event Hierarchies across Modalities
AAAI 2024
Beyond One-Preference-Fits-All Alignment: Multi-Objective Direct Preference Optimization
ACL 2024
Beyond OOD State Actions: Supported Cross-Domain Offline Reinforcement Learning
AAAI 2024
Beyond Optimism: Exploration With Partially Observable Rewards
NeurIPS 2024