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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Papers (including subtopics)
Barely Supervised Learning for Graph-Based Fraud Detection
AAAI 2024
“Barking up the Right Tree”, a GAN-Based Pun Generation Model through Semantic Pruning
COLING 2024
Basque and Spanish Counter Narrative Generation: Data Creation and Evaluation
COLING 2024
Batch-ICL: Effective, Efficient, and Order-Agnostic In-Context Learning
ACL 2024
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference
ICLR 2024
Bayesian Calibration of Win Rate Estimation with LLM Evaluators
EMNLP 2024
Bayesian Domain Adaptation with Gaussian Mixture Domain-Indexing
NeurIPS 2024
Bayesian Example Selection Improves In-Context Learning for Speech, Text and Visual Modalities
EMNLP 2024
Bayesian Exploration of Pre-trained Models for Low-shot Image Classification
CVPR 2024
Bayesian Nonparametrics Meets Data-Driven Distributionally Robust Optimization
NeurIPS 2024
Bayesian Online Learning for Consensus Prediction
AISTATS 2024
Bayesian Prompt Ensembles: Model Uncertainty Estimation for Black-Box Large Language Models
ACL 2024
Bayesian Semi-structured Subspace Inference
AISTATS 2024
BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction
ICLR 2024
BBRC: Brazilian Banking Regulation Corpora
COLING 2024
Beam Enumeration: Probabilistic Explainability For Sample Efficient Self-conditioned Molecular Design
ICLR 2024
Be a Multitude to Itself: A Prompt Evolution Framework for Red Teaming
EMNLP 2024
BeanCounter: A low-toxicity, large-scale, and open dataset of business-oriented text
NeurIPS 2024
Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference
ICLR 2024
BECLR: Batch Enhanced Contrastive Few-Shot Learning
ICLR 2024
Be Confident in What You Know: Bayesian Parameter Efficient Fine-Tuning of Vision Foundation Models
NeurIPS 2024
BEEAR: Embedding-based Adversarial Removal of Safety Backdoors in Instruction-tuned Language Models
EMNLP 2024
BeliefFlow: A Framework for Logic-Based Belief Diffusion via Iterated Belief Change
AAAI 2024
Belief Revision: The Adaptability of Large Language Models Reasoning
EMNLP 2024
Belief-State Query Policies for User-Aligned POMDPs
NeurIPS 2024