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)
Rethinking Correlation Learning via Label Prior for Open Set Domain Adaptation
IJCAI 2024
Rethinking Discount Regularization: New Interpretations, Unintended Consequences, and Solutions for Regularization in Reinforcement Learning
JMLR 2024
Rethinking Exploration in Reinforcement Learning with Effective Metric-Based Exploration Bonus
NeurIPS 2024
Rethinking Fourier Transform from A Basis Functions Perspective for Long-term Time Series Forecasting
NeurIPS 2024
Rethinking Generalizable Face Anti-spoofing via Hierarchical Prototype-guided Distribution Refinement in Hyperbolic Space
CVPR 2024
Rethinking Graph Masked Autoencoders through Alignment and Uniformity
AAAI 2024
Rethinking Imbalance in Image Super-Resolution for Efficient Inference
NeurIPS 2024
Rethinking Inductive Biases for Surface Normal Estimation
CVPR 2024
Rethinking Interactive Image Segmentation with Low Latency High Quality and Diverse Prompts
CVPR 2024
Rethinking Mesh Watermark: Towards Highly Robust and Adaptable Deep 3D Mesh Watermarking
AAAI 2024
Rethinking Misalignment in Vision-Language Model Adaptation from a Causal Perspective
NeurIPS 2024
Rethinking Multi-view Representation Learning via Distilled Disentangling
CVPR 2024
Rethinking Prior Information Generation with CLIP for Few-Shot Segmentation
CVPR 2024
Rethinking Reverse Distillation for Multi-Modal Anomaly Detection
AAAI 2024
Rethinking the Evaluation of In-Context Learning for LLMs
EMNLP 2024
Rethinking the Evaluation of Out-of-Distribution Detection: A Sorites Paradox
NeurIPS 2024
Rethinking the Membrane Dynamics and Optimization Objectives of Spiking Neural Networks
NeurIPS 2024
Rethinking the Objectives of Vector-Quantized Tokenizers for Image Synthesis
CVPR 2024
Rethinking the Paradigm of Content Constraints in Unpaired Image-to-Image Translation
AAAI 2024
Rethinking the Role of Proxy Rewards in Language Model Alignment
EMNLP 2024
Rethinking Transformers Pre-training for Multi-Spectral Satellite Imagery
CVPR 2024
Rethinking Two-Stage Referring Expression Comprehension: A Novel Grounding and Segmentation Method Modulated by Point
AAAI 2024
Rethinking Weight Decay for Robust Fine-Tuning of Foundation Models
NeurIPS 2024
Retrieval-Augmented Code Generation for Situated Action Generation: A Case Study on Minecraft
EMNLP 2024
Retrieval-Augmented Egocentric Video Captioning
CVPR 2024