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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'20
'25
Papers (including subtopics)
Scalable Vision Language Model Training via High Quality Data Curation
ACL 2025
Scalable Vision-Language Understanding and Generation
AAAI 2025
Scale-Aware Contrastive Reverse Distillation for Unsupervised Medical Anomaly Detection
ICLR 2025
Scale-Free Graph-Language Models
ICLR 2025
ScaleLSD: Scalable Deep Line Segment Detection Streamlined
CVPR 2025
ScaleMatch: Multi-scale Consistency Enhancement for Semi-supervised Semantic Segmentation
AAAI 2025
Scaling and evaluating sparse autoencoders
ICLR 2025
Scaling and Taming Adversarial Training with Synthetic Data
ICCV 2025
Scaling Combinatorial Optimization Neural Improvement Heuristics with Online Search and Adaptation
AAAI 2025
Scaling Language-Free Visual Representation Learning
ICCV 2025
Scaling Laws for Multilingual Language Models
ACL 2025
Scaling Laws for Pre-training Agents and World Models
ICML 2025
Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining
ICLR 2025
Scaling, Simplification, and Adaptation: Lessons from Pretraining on Machine-Translated Text
EMNLP 2025
Scaling Text-Rich Image Understanding via Code-Guided Synthetic Multimodal Data Generation
ACL 2025
Scaling Trends in Language Model Robustness
ICML 2025
Scaling Tumor Segmentation: Best Lessons from Real and Synthetic Data
ICCV 2025
Scaling Under-Resourced TTS: A Data-Optimized Framework with Advanced Acoustic Modeling for Thai
ACL 2025
Scaling Up Membership Inference: When and How Attacks Succeed on Large Language Models
NAACL 2025
Scaling up the Banded Matrix Factorization Mechanism for Large Scale Differentially Private ML
ICLR 2025
SCAN: Bootstrapping Contrastive Pre-training for Data Efficiency
ICCV 2025
ScanEZ: Integrating Cognitive Models with Self-Supervised Learning for Spatiotemporal Scanpath Prediction
ACL 2025
Scene-Centric Unsupervised Panoptic Segmentation
CVPR 2025
SceneSplat: Gaussian Splatting-based Scene Understanding with Vision-Language Pretraining
ICCV 2025
SCENIR: Visual Semantic Clarity through Unsupervised Scene Graph Retrieval
ICML 2025