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)
Distance-aware Calibration for Pre-trained Language Models
EMNLP 2024
Distantly Supervised Contrastive Learning for Low-Resource Scripting Language Summarization
COLING 2024
Distantly-Supervised Joint Extraction with Noise-Robust Learning
ACL 2024
Distilling Causal Effect of Data in Continual Few-shot Relation Learning
COLING 2024
Distilling Reliable Knowledge for Instance-Dependent Partial Label Learning
AAAI 2024
Distilling Robustness into Natural Language Inference Models with Domain-Targeted Augmentation
ACL 2024
DistillMIKE: Editing Distillation of Massive In-Context Knowledge Editing in Large Language Models
ACL 2024
DistilVPR: Cross-Modal Knowledge Distillation for Visual Place Recognition
AAAI 2024
Distortion-Disentangled Contrastive Learning
WACV 2024
Distraction is All You Need: Memory-Efficient Image Immunization against Diffusion-Based Image Editing
CVPR 2024
Distributed Estimation on Semi-Supervised Generalized Linear Model
JMLR 2024
Distributionally Robust Model-Based Offline Reinforcement Learning with Near-Optimal Sample Complexity
JMLR 2024
Distributionally Robust Model-based Reinforcement Learning with Large State Spaces
AISTATS 2024
Distributionally Robust Off-Dynamics Reinforcement Learning: Provable Efficiency with Linear Function Approximation
AISTATS 2024
Distributionally Robust Performative Prediction
NeurIPS 2024
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms
NeurIPS 2024
Distributional Off-Policy Evaluation for Slate Recommendations
AAAI 2024
Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF
ICLR 2024
Distributional regression: CRPS-error bounds for model fitting, model selection and convex aggregation
NeurIPS 2024
Distributional Reinforcement Learning with Regularized Wasserstein Loss
NeurIPS 2024
Distributional Successor Features Enable Zero-Shot Policy Optimization
NeurIPS 2024
Distribution-Aware Data Expansion with Diffusion Models
NeurIPS 2024
Distribution-aware Knowledge Prototyping for Non-exemplar Lifelong Person Re-identification
CVPR 2024
Distribution Guidance Network for Weakly Supervised Point Cloud Semantic Segmentation
NeurIPS 2024
Distribution-Independent Cell Type Identification for Single-Cell RNA-seq Data
IJCAI 2024