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)
Infrared-Visible Cross-Modal Person Re-Identification with an X Modality
AAAI 2020
Infusing Disease Knowledge into BERT for Health Question Answering, Medical Inference and Disease Name Recognition
EMNLP 2020
Injecting Numerical Reasoning Skills into Language Models
ACL 2020
iNLTK: Natural Language Toolkit for Indic Languages
EMNLP 2020
In Neural Machine Translation, What Does Transfer Learning Transfer?
ACL 2020
In search of isoglosses: continuous and discrete language embeddings in Slavic historical phonology
ACL 2020
Insertion-Based Modeling for End-to-End Automatic Speech Recognition
Interspeech 2020
INSET: Sentence Infilling with INter-SEntential Transformer
ACL 2020
Instance-Adaptive Graph for EEG Emotion Recognition
AAAI 2020
Instance-Aware, Context-Focused, and Memory-Efficient Weakly Supervised Object Detection
CVPR 2020
Instance-Aware Image Colorization
CVPR 2020
Instance Enhancement Batch Normalization: An Adaptive Regulator of Batch Noise
AAAI 2020
Instance Selection for GANs
NeurIPS 2020
Instance-wise Feature Grouping
NeurIPS 2020
Integrating Deep Learning with Logic Fusion for Information Extraction
AAAI 2020
Integrating Multimodal Information in Large Pretrained Transformers
ACL 2020
Integrating Relation Constraints with Neural Relation Extractors
AAAI 2020
Intelligent Analyses on Storytelling for Impact Measurement
EMNLP 2020
Interactive Dual Generative Adversarial Networks for Image Captioning
AAAI 2020
Interactive Multi-Label CNN Learning With Partial Labels
CVPR 2020
Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work?
ACL 2020
Internet of Things (IoT) Discovery Using Deep Neural Networks
WACV 2020
Interpretable Entity Representations through Large-Scale Typing
EMNLP 2020
Interpretations are Useful: Penalizing Explanations to Align Neural Networks with Prior Knowledge
ICML 2020
Interpreting Pretrained Contextualized Representations via Reductions to Static Embeddings
ACL 2020