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)
Two-Stage Evolutionary Reinforcement Learning for Enhancing Exploration and Exploitation
AAAI 2024
Two Tales of Single-Phase Contrastive Hebbian Learning
ICML 2024
Typos that Broke the RAG’s Back: Genetic Attack on RAG Pipeline by Simulating Documents in the Wild via Low-level Perturbations
EMNLP 2024
UDA: A Benchmark Suite for Retrieval Augmented Generation in Real-World Document Analysis
NeurIPS 2024
UDON: Universal Dynamic Online distillatioN for generic image representations
NeurIPS 2024
UDPM: Upsampling Diffusion Probabilistic Models
NeurIPS 2024
UFCNet: Unsupervised Network based on Fourier transform and Convolutional attention for Oracle Character Recognition
ACL 2024
UFORecon: Generalizable Sparse-View Surface Reconstruction from Arbitrary and Unfavorable Sets
CVPR 2024
UltraLink: An Open-Source Knowledge-Enhanced Multilingual Supervised Fine-tuning Dataset
ACL 2024
UltraSparseBERT: 99% Conditionally Sparse Language Modelling
ACL 2024
UMA: Facilitating Backdoor Scanning via Unlearning-Based Model Ablation
AAAI 2024
UMB: Understanding Model Behavior for Open-World Object Detection
NeurIPS 2024
Unbiased Faster R-CNN for Single-source Domain Generalized Object Detection
CVPR 2024
Unbiased Multi-Label Learning from Crowdsourced Annotations
ICML 2024
Uncertainty-aware Action Decoupling Transformer for Action Anticipation
CVPR 2024
Uncertainty-aware Fine-tuning of Segmentation Foundation Models
NeurIPS 2024
Uncertainty-Aware GAN for Single Image Super Resolution
AAAI 2024
Uncertainty-Aware Yield Prediction with Multimodal Molecular Features
AAAI 2024
Uncertainty Estimation in Instance Segmentation With Star-Convex Shapes
WACV 2024
Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor Defense
NeurIPS 2024
Understanding Addition in Transformers
ICLR 2024
Understanding Bias in Large-Scale Visual Datasets
NeurIPS 2024
Understanding Dark Scenes by Contrasting Multi-Modal Observations
WACV 2024
Understanding Distributed Representations of Concepts in Deep Neural Networks without Supervision
AAAI 2024
Understanding Generalizability of Diffusion Models Requires Rethinking the Hidden Gaussian Structure
NeurIPS 2024