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)
What Really Matters in Many-Shot Attacks? An Empirical Study of Long-Context Vulnerabilities in LLMs
ACL 2025
What’s in a prompt? Language models encode literary style in prompt embeddings
EMNLP 2025
What's in the Image? A Deep-Dive into the Vision of Vision Language Models
CVPR 2025
What's Making That Sound Right Now? Video-centric Audio-Visual Localization
ICCV 2025
What to Distill? Fast Knowledge Distillation with Adaptive Sampling
ICCV 2025
When2Call: When (not) to Call Tools
NAACL 2025
When and How Does CLIP Enable Domain and Compositional Generalization?
ICML 2025
When and How to Augment Your Input: Question Routing Helps Balance the Accuracy and Efficiency of Large Language Models
NAACL 2025
When and Where do Data Poisons Attack Textual Inversion?
ICCV 2025
When Big Models Train Small Ones: Label-Free Model Parity Alignment for Efficient Visual Question Answering using Small VLMs
EMNLP 2025
When Can We Approximate Wide Contrastive Models with Neural Tangent Kernels and Principal Component Analysis?
AAAI 2025
When Cars Meet Drones: Hyperbolic Federated Learning for Source-Free Domain Adaptation in Adverse Weather
WACV 2025
When Data-Free Knowledge Distillation Meets Non-Transferable Teacher: Escaping Out-of-Distribution Trap is All You Need
ICML 2025
When Dynamic Data Selection Meets Data Augmentation: Achieving Enhanced Training Acceleration
ICML 2025
When Hypergraph Meets Heterophily: New Benchmark Datasets and Baseline
AAAI 2025
When Long Helps Short: How Context Length in Supervised Fine-tuning Affects Behavior of Large Language Models
EMNLP 2025
When natural language is not enough: The limits of in-context learning demonstrations in multilingual reasoning
NAACL 2025
When Should We Prefer State-to-Visual DAgger over Visual Reinforcement Learning?
AAAI 2025
When the Future Becomes the Past: Taming Temporal Correspondence for Self-supervised Video Representation Learning
CVPR 2025
When The MOS Predictor Asks For Training Annotation In Cross Lingual/Domain Adaptation
Interspeech 2025
When to Continue Thinking: Adaptive Thinking Mode Switching for Efficient Reasoning
EMNLP 2025
When to Learn and When to Stop: Quitting at the Optimal Time (Student Abstract)
AAAI 2025
When to Speak, When to Abstain: Contrastive Decoding with Abstention
ACL 2025
When Truthful Representations Flip Under Deceptive Instructions?
EMNLP 2025
When Visual State Space Model Meets Backdoor Attacks
WACV 2025