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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'10
'15
'20
'25
Papers (including subtopics)
The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning
ICLR 2024
The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better
NeurIPS 2024
The Unreasonable Effectiveness of Easy Training Data for Hard Tasks
ACL 2024
The Unreasonable Effectiveness of Pre-Trained Features for Camera Pose Refinement
CVPR 2024
The Value of Reward Lookahead in Reinforcement Learning
NeurIPS 2024
The Vedic Compound Dataset
COLING 2024
Think Before You Duel: Understanding Complexities of Preference Learning under Constrained Resources
AISTATS 2024
Think Global, Adapt Local: Learning Locally Adaptive K-Nearest Neighbor Kernel Density Estimators
AISTATS 2024
“Thinking” Fair and Slow: On the Efficacy of Structured Prompts for Debiasing Language Models
EMNLP 2024
Thinking Outside of the Differential Privacy Box: A Case Study in Text Privatization with Language Model Prompting
EMNLP 2024
Think Twice Before Selection: Federated Evidential Active Learning for Medical Image Analysis with Domain Shifts
CVPR 2024
Think Twice: Perspective-Taking Improves Large Language Models’ Theory-of-Mind Capabilities
ACL 2024
Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox
NeurIPS 2024
Thompson Sampling for Real-Valued Combinatorial Pure Exploration of Multi-Armed Bandit
AAAI 2024
Thompson Sampling Itself is Differentially Private
AISTATS 2024
Threaten Spiking Neural Networks through Combining Rate and Temporal Information
ICLR 2024
Three Heads Are Better than One: Complementary Experts for Long-Tailed Semi-supervised Learning
AAAI 2024
Three Heads Are Better than One: Improving Cross-Domain NER with Progressive Decomposed Network
AAAI 2024
TI2V-Zero: Zero-Shot Image Conditioning for Text-to-Video Diffusion Models
CVPR 2024
TiC-CLIP: Continual Training of CLIP Models
ICLR 2024
Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective
NeurIPS 2024
Tight Rates for Bandit Control Beyond Quadratics
NeurIPS 2024
TIKP: Text-to-Image Knowledge Preservation for Continual Semantic Segmentation
AAAI 2024
Time-Aware Knowledge Representations of Dynamic Objects with Multidimensional Persistence
AAAI 2024
TimeBench: A Comprehensive Evaluation of Temporal Reasoning Abilities in Large Language Models
ACL 2024