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Learning Types

32,670 papers (1 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Representation Learning (5,307) Multimodal Learning (3,969) Self-Supervised Learning (3,492) Transfer Learning (2,890) Adversarial Learning (2,199) Deep Learning (1,883) Contrastive Learning (1,730) Reinforcement Learning (1,500) Knowledge Distillation (1,494) Fine-Tuning (1,117) Multi-Task Learning (1,069) Domain Adaptation (977) Zero-Shot Learning (758) Unsupervised Learning (734) Few-Shot Learning (694) Classification (621) Retrieval-Augmented Generation (606) Data Augmentation (583) Semi-Supervised Learning (450) Weakly Supervised Learning (429) Continual Learning (408) In-Context Learning (387) Sequence Modeling (375) Meta-Learning (252) Metric Learning (232) Ensemble Learning (223) Federated Learning (215) Multi-Lingual Learning (199) Robustness (197) Parameter-Efficient Fine-Tuning (190) Imitation Learning (180) Prompt Engineering (170) Chain-of-Thought Reasoning (153) Curriculum Learning (146) Synthetic Data Generation (143) Reinforcement Learning from Human Feedback (141) Multi-Label Classification (123) Regression (117) Generative Model (109) Semantic Segmentation (106) Domain Generalization (105) Uncertainty Quantification (98) Controllable Generation (93) Text Generation (86) Neural Architecture Search (80) Object Detection (80) Image Generation (79) Multi-Agent Systems (76) Feature Learning (74) Preference Learning (73) Machine Translation (71) Out-of-Distribution Detection (68) Machine Unlearning (63) Generation (61) Reasoning (54) Multi-View Learning (53) Time Series (52) Instruction Tuning (50) Distributed Learning (50) Image Restoration (49) Chain-of-Thought (48) Active Learning (47) Text Classification (43) Distribution Shift (43) Structured Prediction (42) Clustering (41) Image Classification (40) Model Merging (37) Sparse Learning (36) Sequence Labeling (36) Multi-Instance Learning (35) Anomaly Detection (33) Image Processing (33) Code Generation (31) Fairness (30) Robust Learning (28) Multi-Domain Learning (27) Supervised Learning (26) Model-Based RL (25) Natural Language Generation (24) Privacy (21) Multi-Objective Optimization (19) Multi-Scale Learning (19) Neural Machine Translation (18) Causal Inference (14) Instance Segmentation (9) Interactive Learning (9) Multi-Label Learning (9) Multi-Source Learning (9) Multi-Class Classification (8)

Papers per year

38
179
3,018
5,737
'10
'15
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'25

Papers (including subtopics)

Distilling a speech and music encoder with task arithmetic Interspeech 2025 Distilling Cross-Modal Knowledge into Domain-Specific Retrievers for Enhanced Industrial Document Understanding EMNLP 2025 Distilling Knowledge from Heterogeneous Architectures for Semantic Segmentation AAAI 2025 Distilling Many-Shot In-Context Learning into a Cheat Sheet EMNLP 2025 Distilling Multi-modal Large Language Models for Autonomous Driving CVPR 2025 Distilling Spatially-Heterogeneous Distortion Perception for Blind Image Quality Assessment CVPR 2025 Distilling Structured Rationale from Large Language Models to Small Language Models for Abstractive Summarization AAAI 2025 Distributed Cascaded Manifold Hashing Network for Compact Image Set Representation IJCAI 2025 Distributional Off-policy Evaluation with Bellman Residual Minimization AISTATS 2025 Distribution-Driven Dense Retrieval: Modeling Many-to-One Query-Document Relationship AAAI 2025 Distribution Prompting: Understanding the Expressivity of Language Models Through the Next-Token Distributions They Can Produce EMNLP 2025 Distribution Prototype Diffusion Learning for Open-set Supervised Anomaly Detection CVPR 2025 DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations CVPR 2025 DiTCtrl: Exploring Attention Control in Multi-Modal Diffusion Transformer for Tuning-Free Multi-Prompt Longer Video Generation CVPR 2025 Diverse, not Short: A Length-Controlled Data Selection Strategy for Improving Response Diversity of Language Models EMNLP 2025 Diverse Policies Recovering via Pointwise Mutual Information Weighted Imitation Learning ICLR 2025 Diverse Rare Sample Generation with Pretrained GANs AAAI 2025 Diversity-Enhanced Distribution Alignment for Dataset Distillation ICCV 2025 Diversity-oriented Data Augmentation with Large Language Models ACL 2025 DivGCL: A Graph Contrastive Learning Model for Diverse Recommendation AAAI 2025 Divide and Conquer: Heterogeneous Noise Integration for Diffusion-based Adversarial Purification CVPR 2025 Divide and Orthogonalize: Efficient Continual Learning with Local Model Space Projection UAI 2025 Divide-Then-Aggregate: An Efficient Tool Learning Method via Parallel Tool Invocation ACL 2025 Divide-Then-Align: Honest Alignment based on the Knowledge Boundary of RAG ACL 2025 Diving into the Fusion of Monocular Priors for Generalized Stereo Matching ICCV 2025