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
'5
'10
'15
'20
'25
Papers (including subtopics)
On the Effects of Fairness to Adversarial Vulnerability
IJCAI 2024
On the Essence and Prospect: An Investigation of Alignment Approaches for Big Models
IJCAI 2024
On the Estimation of Image-matching Uncertainty in Visual Place Recognition
CVPR 2024
On the Evaluation of Speech Foundation Models for Spoken Language Understanding
ACL 2024
On the Expressivity of Recurrent Neural Cascades
AAAI 2024
On the Faithfulness of Vision Transformer Explanations
CVPR 2024
On the Fragility of Active Learners for Text Classification
EMNLP 2024
On the Generalization Ability of Unsupervised Pretraining
AISTATS 2024
On the Generalization of Training-based ChatGPT Detection Methods
EMNLP 2024
On the Growth of Mistakes in Differentially Private Online Learning: A Lower Bound Perspective
COLT 2024
On the Hallucination in Simultaneous Machine Translation
ACL 2024
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
JMLR 2024
On the impact of several regularization techniques on label noise robustness of self-supervised speaker verification systems
Interspeech 2024
On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods
AAAI 2024
On the Importance of Large Objects in CNN Based Object Detection Algorithms
WACV 2024
On the In-context Generation of Language Models
EMNLP 2024
On the Intractability to Synthesize Factual Inconsistencies in Summarization
EACL 2024
On the Language Encoder of Contrastive Cross-modal Models
ACL 2024
On the Learnability of Out-of-distribution Detection
JMLR 2024
On the Limited Generalization Capability of the Implicit Reward Model Induced by Direct Preference Optimization
EMNLP 2024
On the Minimax Regret for Contextual Linear Bandits and Multi-Armed Bandits with Expert Advice
NeurIPS 2024
On the Misspecification of Linear Assumptions in Synthetic Controls
AISTATS 2024
On the Model-Misspecification in Reinforcement Learning
AISTATS 2024
On the Necessity of Collaboration for Online Model Selection with Decentralized Data
NeurIPS 2024
On the Noise Robustness of In-Context Learning for Text Generation
NeurIPS 2024