Learning Types
32,670 papers (1 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Representation Learning (5,307)
Multimodal Learning (3,969)
Self-Supervised Learning (3,492)
Transfer Learning (2,890)
Adversarial Learning (2,199)
Deep Learning (1,883)
Contrastive Learning (1,730)
Reinforcement Learning (1,500)
Knowledge Distillation (1,494)
Fine-Tuning (1,117)
Multi-Task Learning (1,069)
Domain Adaptation (977)
Zero-Shot Learning (758)
Unsupervised Learning (734)
Few-Shot Learning (694)
Classification (621)
Retrieval-Augmented Generation (606)
Data Augmentation (583)
Semi-Supervised Learning (450)
Weakly Supervised Learning (429)
Continual Learning (408)
In-Context Learning (387)
Sequence Modeling (375)
Meta-Learning (252)
Metric Learning (232)
Ensemble Learning (223)
Federated Learning (215)
Multi-Lingual Learning (199)
Robustness (197)
Parameter-Efficient Fine-Tuning (190)
Imitation Learning (180)
Prompt Engineering (170)
Chain-of-Thought Reasoning (153)
Curriculum Learning (146)
Synthetic Data Generation (143)
Reinforcement Learning from Human Feedback (141)
Multi-Label Classification (123)
Regression (117)
Generative Model (109)
Semantic Segmentation (106)
Domain Generalization (105)
Uncertainty Quantification (98)
Controllable Generation (93)
Text Generation (86)
Neural Architecture Search (80)
Object Detection (80)
Image Generation (79)
Multi-Agent Systems (76)
Feature Learning (74)
Preference Learning (73)
Machine Translation (71)
Out-of-Distribution Detection (68)
Machine Unlearning (63)
Generation (61)
Reasoning (54)
Multi-View Learning (53)
Time Series (52)
Instruction Tuning (50)
Distributed Learning (50)
Image Restoration (49)
Chain-of-Thought (48)
Active Learning (47)
Text Classification (43)
Distribution Shift (43)
Structured Prediction (42)
Clustering (41)
Image Classification (40)
Model Merging (37)
Sparse Learning (36)
Sequence Labeling (36)
Multi-Instance Learning (35)
Anomaly Detection (33)
Image Processing (33)
Code Generation (31)
Fairness (30)
Robust Learning (28)
Multi-Domain Learning (27)
Supervised Learning (26)
Model-Based RL (25)
Natural Language Generation (24)
Privacy (21)
Multi-Objective Optimization (19)
Multi-Scale Learning (19)
Neural Machine Translation (18)
Causal Inference (14)
Instance Segmentation (9)
Interactive Learning (9)
Multi-Label Learning (9)
Multi-Source Learning (9)
Multi-Class Classification (8)
Papers per year
1
22
25
29
26
38
46
60
109
129
179
310
686
1,294
2,286
3,018
3,254
3,930
4,067
4,819
5,737
2,605
'10
'15
'20
'25
Papers (including subtopics)
Geometric Image Correspondence Verification by Dense Pixel Matching
WACV 2020
Geometric Structure Based and Regularized Depth Estimation From 360 Indoor Imagery
CVPR 2020
Geometry-aware domain adaptation for unsupervised alignment of word embeddings
ACL 2020
Geometry-Driven Self-Supervised Method for 3D Human Pose Estimation
AAAI 2020
Getting Closer to AI Complete Question Answering: A Set of Prerequisite Real Tasks
AAAI 2020
Global Co-occurrence Feature Learning and Active Coordinate System Conversion for Skeleton-based Action Recognition
WACV 2020
Global-Local Bidirectional Reasoning for Unsupervised Representation Learning of 3D Point Clouds
CVPR 2020
Global-Local GCN: Large-Scale Label Noise Cleansing for Face Recognition
CVPR 2020
Global Texture Enhancement for Fake Face Detection in the Wild
CVPR 2020
Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Search
NeurIPS 2020
Glyph2Vec: Learning Chinese Out-of-Vocabulary Word Embedding from Glyphs
ACL 2020
GMAN: A Graph Multi-Attention Network for Traffic Prediction
AAAI 2020
GNNGuard: Defending Graph Neural Networks against Adversarial Attacks
NeurIPS 2020
GoEmotions: A Dataset of Fine-Grained Emotions
ACL 2020
Go Figure! Multi-task transformer-based architecture for metaphor detection using idioms: ETS team in 2020 metaphor shared task
ACL 2020
Go From the General to the Particular: Multi-Domain Translation with Domain Transformation Networks
AAAI 2020
Going Beyond T-SNE: Exposing whatlies in Text Embeddings
EMNLP 2020
Going Deeper With Lean Point Networks
CVPR 2020
Going Deep: Graph Convolutional Ladder-Shape Networks
AAAI 2020
Good-Enough Compositional Data Augmentation
ACL 2020
Go Wide, Then Narrow: Efficient Training of Deep Thin Networks
ICML 2020
Gradient-Aware Model-Based Policy Search
AAAI 2020
Gradually Vanishing Bridge for Adversarial Domain Adaptation
CVPR 2020
Graduate Employment Prediction with Bias
AAAI 2020
Grammatical Error Correction Using Pseudo Learner Corpus Considering Learner’s Error Tendency
ACL 2020