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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'10
'15
'20
'25
Papers (including subtopics)
Re-thinking Data Availability Attacks Against Deep Neural Networks
CVPR 2024
Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective
AAAI 2024
Rethinking Discount Regularization: New Interpretations, Unintended Consequences, and Solutions for Regularization in Reinforcement Learning
JMLR 2024
Rethinking Evaluation Methods for Machine Unlearning
EMNLP 2024
Rethinking Exploration in Reinforcement Learning with Effective Metric-Based Exploration Bonus
NeurIPS 2024
Rethinking FID: Towards a Better Evaluation Metric for Image Generation
CVPR 2024
Rethinking Graph Masked Autoencoders through Alignment and Uniformity
AAAI 2024
Rethinking Guidance Information to Utilize Unlabeled Samples: A Label Encoding Perspective
ICML 2024
Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment
NeurIPS 2024
Rethinking Label Poisoning for GNNs: Pitfalls and Attacks
ICLR 2024
Rethinking LLM Memorization through the Lens of Adversarial Compression
NeurIPS 2024
Rethinking Model Ensemble in Transfer-based Adversarial Attacks
ICLR 2024
Rethinking Multi-domain Generalization with A General Learning Objective
CVPR 2024
Rethinking Multi-view Representation Learning via Distilled Disentangling
CVPR 2024
Rethinking Negative Instances for Generative Named Entity Recognition
ACL 2024
Rethinking Pragmatics in Large Language Models: Towards Open-Ended Evaluation and Preference Tuning
EMNLP 2024
Rethinking Prior Information Generation with CLIP for Few-Shot Segmentation
CVPR 2024
Rethinking Reverse Distillation for Multi-Modal Anomaly Detection
AAAI 2024
Rethinking Robustness Assessment: Adversarial Attacks on Learning-based Quadrupedal Locomotion Controllers
RSS 2024
Rethinking Robustness of Model Attributions
AAAI 2024
Rethinking Score Distillation as a Bridge Between Image Distributions
NeurIPS 2024
Rethinking Skill Extraction in the Job Market Domain using Large Language Models
EACL 2024
Rethinking Task-Oriented Dialogue Systems: From Complex Modularity to Zero-Shot Autonomous Agent
ACL 2024
Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?
ACL 2024
Rethinking the Evaluation of In-Context Learning for LLMs
EMNLP 2024