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
1
22
25
29
26
38
46
60
109
129
179
310
686
1,294
2,286
3,018
3,254
3,930
4,067
4,819
5,737
2,605
'10
'15
'20
'25
Papers (including subtopics)
Evidential Uncertainty-Guided Mitochondria Segmentation for 3D EM Images
AAAI 2024
EVIT: Event-Oriented Instruction Tuning for Event Reasoning
ACL 2024
Evolutionary Contrastive Distillation for Language Model Alignment
EMNLP 2024
Evolution-Inspired Loss Functions for Protein Representation Learning
ICML 2024
EvoR: Evolving Retrieval for Code Generation
EMNLP 2024
EVS-assisted Joint Deblurring Rolling-Shutter Correction and Video Frame Interpolation through Sensor Inverse Modeling
CVPR 2024
EvTexture: Event-driven Texture Enhancement for Video Super-Resolution
ICML 2024
ExACT: Language-guided Conceptual Reasoning and Uncertainty Estimation for Event-based Action Recognition and More
CVPR 2024
EXAMS-V: A Multi-Discipline Multilingual Multimodal Exam Benchmark for Evaluating Vision Language Models
ACL 2024
ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis
ICLR 2024
Existence and Minimax Theorems for Adversarial Surrogate Risks in Binary Classification
JMLR 2024
Existence Is Chaos: Enhancing 3D Human Motion Prediction with Uncertainty Consideration
AAAI 2024
ExMap: Leveraging Explainability Heatmaps for Unsupervised Group Robustness to Spurious Correlations
CVPR 2024
ExMatch: Self-guided Exploitation for Semi-Supervised Learning with Scarce Labeled Samples
ECCV 2024
Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning
CVPR 2024
Expanding Expressiveness of Diffusion Models With Limited Data via Self-Distillation Based Fine-Tuning
WACV 2024
Expected flow networks in stochastic environments and two-player zero-sum games
ICLR 2024
Expediting Contrastive Language-Image Pretraining via Self-Distilled Encoders
AAAI 2024
Experiential Co-Learning of Software-Developing Agents
ACL 2024
Experimental Contexts Can Facilitate Robust Semantic Property Inference in Language Models, but Inconsistently
EMNLP 2024
Explainable Earnings Call Representation Learning (Student Abstract)
AAAI 2024
Explaining and Improving Contrastive Decoding by Extrapolating the Probabilities of a Huge and Hypothetical LM
EMNLP 2024
Explaining CLIP's Performance Disparities on Data from Blind/Low Vision Users
CVPR 2024
Explaining the Implicit Neural Canvas: Connecting Pixels to Neurons by Tracing their Contributions
CVPR 2024
Explanation-aware Soft Ensemble Empowers Large Language Model In-context Learning
ACL 2024