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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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20
220
477
4,652
9,258
2000
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Papers (including subtopics)

Learning Fair Representations with Kolmogorov-Arnold Networks AAAI 2026 Learning from Biased and Costly Data Sources: Minimax-optimal Data Collection under a Budget (extended abstract) COLT 2026 Learning from Equivalence Queries, Revisited COLT 2026 Learning from Imperfect Data: Incremental Learning and Few-shot Learning AAAI 2026 Learning from Near-Misses: Error-Aware Contrastive Few-Shot Learning for NL2Formula ACL 2026 Learning from Noisy Supervision: A Denoising-Debiasing Framework for Weakly Supervised Video Anomaly Detection CVPR 2026 Learning from Reasoning Failures via Synthetic Data Generation AAAI 2026 Learning from Scoring Disagreements: Contrastive Error Mining for Efficient and Robust LLM-based Assessment AAAI 2026 Learning from Synthetic Data via Provenance-Based Input Gradient Guidance CVPR 2026 Learning from the Undesirable: Robust Adaptation of Language Models Without Forgetting AAAI 2026 Learning from Unknown for Open-Set Test-Time Adaptation WACV 2026 Learning Ising Models from Evolutions (Extended Abstract) COLT 2026 Learning More from Less: Resource-Constrained Generative AI for Classification, Generation, and Personalization AAAI 2026 Learning Nested Named Entity Recognition from Flat Annotations EACL 2026 Learning Nonholonomic Dynamics with Constraint Discovery L4DC 2026 Learning Periodic Strategies in Blocking Bandits Is as Hard as Bandits with Switching Costs COLT 2026 Learning Stable Digraphs from Sparse-Input Linear Structural Causal Models UAI 2026 Learning Structure-Aware Foundational Representation of Rat Testicular Tubules Using Multiple Instance Learning MIDL 2026 Learning the Latent Structure: A Feature-Centric Approach to Graph Data Augmentation AAAI 2026 Learning Time in Static Classifiers AAAI 2026 Learning to Act Through Contact: A Unified View of Multi-Task Robot Learning L4DC 2026 Learning to Cluster Rare Cell Types: Implicit Semantic Data Augmentation for Spatial Multi-modal Omics Analysis AAAI 2026 Learning to Compress: Unlocking the Potential of Large Language Models for Text Representation AAAI 2026 Learning to Deliberate: Meta-policy Collaboration for Agentic LLMs with Multi-agent Reinforcement Learning AAAI 2026 Learning to Explore: Policy-Guided Outlier Synthesis for Graph Out-of-Distribution Detection AAAI 2026