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
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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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Papers (including subtopics)
Selectively Informative Description can Reduce Undesired Embedding Entanglements in Text-to-Image Personalization
CVPR 2024
Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives
ICLR 2024
Selective Prompting Tuning for Personalized Conversations with LLMs
ACL 2024
Self-Adaptive Reality-Guided Diffusion for Artifact-Free Super-Resolution
CVPR 2024
Self-Alignment with Instruction Backtranslation
ICLR 2024
Self-AMPLIFY: Improving Small Language Models with Self Post Hoc Explanations
EMNLP 2024
Self-Annotated 3D Geometric Learning for Smeared Points Removal
WACV 2024
Self-Bootstrapped Visual-Language Model for Knowledge Selection and Question Answering
EMNLP 2024
Self-Calibrated Tuning of Vision-Language Models for Out-of-Distribution Detection
NeurIPS 2024
SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning
ICLR 2024
Self-Cleaning: Improving a Named Entity Recognizer Trained on Noisy Data with a Few Clean Instances
NAACL 2024
SelfCodeAlign: Self-Alignment for Code Generation
NeurIPS 2024
Self-Compatibility: Evaluating Causal Discovery without Ground Truth
AISTATS 2024
Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction
ICML 2024
Self-Consuming Generative Models with Curated Data Provably Optimize Human Preferences
NeurIPS 2024
Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning
ACL 2024
Self-Distillation for Model Stacking Unlocks Cross-Lingual NLU in 200+ Languages
EMNLP 2024
Self-Distilled Depth Refinement with Noisy Poisson Fusion
NeurIPS 2024
Self-Distilled Masked Auto-Encoders are Efficient Video Anomaly Detectors
CVPR 2024
Self-Evaluation of Large Language Model based on Glass-box Features
EMNLP 2024
Self-Evolving GPT: A Lifelong Autonomous Experiential Learner
ACL 2024
Self-Explore: Enhancing Mathematical Reasoning in Language Models with Fine-grained Rewards
EMNLP 2024
Self-generated Replay Memories for Continual Neural Machine Translation
NAACL 2024
SelfGeo: Self-supervised and Geodesic-consistent Estimation of Keypoints on Deformable Shapes
ECCV 2024
Self-Guided Masked Autoencoder
NeurIPS 2024