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)
OneLLM: One Framework to Align All Modalities with Language
CVPR 2024
One-Prompt to Segment All Medical Images
CVPR 2024
One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models
CVPR 2024
One Self-Configurable Model to Solve Many Abstract Visual Reasoning Problems
AAAI 2024
One-Shot Machine Unlearning with Mnemonic Code
ACML 2024
One Step Closer to Unbiased Aleatoric Uncertainty Estimation
AAAI 2024
One-Step Effective Diffusion Network for Real-World Image Super-Resolution
NeurIPS 2024
One-to-many testing for code generation from (just) natural language
EMNLP 2024
One-to-Multiple: A Progressive Style Transfer Unsupervised Domain-Adaptive Framework for Kidney Tumor Segmentation
NeurIPS 2024
One-to-Normal: Anomaly Personalization for Few-shot Anomaly Detection
NeurIPS 2024
On Feature Learning in Structured State Space Models
NeurIPS 2024
On Giant's Shoulders: Effortless Weak to Strong by Dynamic Logits Fusion
NeurIPS 2024
On Improving Repository-Level Code QA for Large Language Models
ACL 2024
On Learning Discriminative Features from Synthesized Data for Self-Supervised Fine-Grained Visual Recognition
ECCV 2024
On Learning Frequency-Instance Correlations by Model-Agnostic Training for Synthetic Speech Detection
ACML 2024
Online Continuous Generalized Category Discovery
ECCV 2024
OnlineTAS: An Online Baseline for Temporal Action Segmentation
NeurIPS 2024
On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability
NeurIPS 2024
On Scaling Up a Multilingual Vision and Language Model
CVPR 2024
On Stronger Computational Separations Between Multimodal and Unimodal Machine Learning
ICML 2024
On task-relevant loss functions in meta-reinforcement learning
L4DC 2024
On the Comparison between Multi-modal and Single-modal Contrastive Learning
NeurIPS 2024
On the Concept Trustworthiness in Concept Bottleneck Models
AAAI 2024
On the connection between Noise-Contrastive Estimation and Contrastive Divergence
AISTATS 2024
On the Convergence of an Adaptive Momentum Method for Adversarial Attacks
AAAI 2024