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)
Learning to Paraphrase for Alignment with LLM Preference
EMNLP 2024
Learning to Pivot as a Smart Expert
AAAI 2024
Learning to Rank in Generative Retrieval
AAAI 2024
Learning to Rank Patches for Unbiased Image Redundancy Reduction
CVPR 2024
Learning to Read Analog Gauges from Synthetic Data
WACV 2024
Learning to Refine with Fine-Grained Natural Language Feedback
EMNLP 2024
Learning to Rematch Mismatched Pairs for Robust Cross-Modal Retrieval
CVPR 2024
Learning to Retrieve Iteratively for In-Context Learning
EMNLP 2024
Learning to Segment Referred Objects from Narrated Egocentric Videos
CVPR 2024
Learning to Shape In-distribution Feature Space for Out-of-distribution Detection
NeurIPS 2024
Learning to Solve the Constrained Most Probable Explanation Task in Probabilistic Graphical Models
AISTATS 2024
Learning to Trust Your Feelings: Leveraging Self-awareness in LLMs for Hallucination Mitigation
ACL 2024
Learning to Visually Localize Sound Sources from Mixtures without Prior Source Knowledge
CVPR 2024
Learning Transferable Features for Implicit Neural Representations
NeurIPS 2024
Learning Transferable Negative Prompts for Out-of-Distribution Detection
CVPR 2024
Learning Versatile Skills with Curriculum Masking
NeurIPS 2024
Learning Vision from Models Rivals Learning Vision from Data
CVPR 2024
Learning Visual Abstract Reasoning through Dual-Stream Networks
AAAI 2024
Learning When to Retrieve, What to Rewrite, and How to Respond in Conversational QA
EMNLP 2024
Learning with 3D rotations, a hitchhiker’s guide to SO(3)
ICML 2024
Learning without Exact Guidance: Updating Large-scale High-resolution Land Cover Maps from Low-resolution Historical Labels
CVPR 2024
Learning with Structural Labels for Learning with Noisy Labels
CVPR 2024
Learning with Unreliability: Fast Few-shot Voxel Radiance Fields with Relative Geometric Consistency
CVPR 2024
Learning World Models for Unconstrained Goal Navigation
NeurIPS 2024
Learn it or Leave it: Module Composition and Pruning for Continual Learning
ACL 2024