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)
FAKD: Feature Augmented Knowledge Distillation for Semantic Segmentation
WACV 2024
FakeSound: Deepfake General Audio Detection
Interspeech 2024
FAME: Towards Factual Multi-Task Model Editing
EMNLP 2024
FanLoRA: Fantastic LoRAs and Where to Find Them in Large Language Model Fine-tuning
EMNLP 2024
FashionERN: Enhance-and-Refine Network for Composed Fashion Image Retrieval
AAAI 2024
Fast Adaptation for Human Pose Estimation via Meta-Optimization
CVPR 2024
FastAdaSP: Multitask-Adapted Efficient Inference for Large Speech Language Model
EMNLP 2024
Fast and Knowledge-Free Deep Learning for General Game Playing (Student Abstract)
AAAI 2024
Fast Best-of-N Decoding via Speculative Rejection
NeurIPS 2024
FastCLIPstyler: Optimisation-Free Text-Based Image Style Transfer Using Style Representations
WACV 2024
Fast Context-Based Low-Light Image Enhancement via Neural Implicit Representations
ECCV 2024
Faster Neighborhood Attention: Reducing the O(n^2) Cost of Self Attention at the Threadblock Level
NeurIPS 2024
FastGAS: Fast Graph-based Annotation Selection for In-Context Learning
ACL 2024
Fast Imitation via Behavior Foundation Models
ICLR 2024
Fast Inter-frame Motion Prediction for Compressed Dynamic Point Cloud Attribute Enhancement
AAAI 2024
FASTopic: Pretrained Transformer is a Fast, Adaptive, Stable, and Transferable Topic Model
NeurIPS 2024
Fast Randomized Low-Rank Adaptation of Pre-trained Language Models with PAC Regularization
ACL 2024
Fast Streaming Transducer ASR Prototyping via Knowledge Distillation with Whisper
EMNLP 2024
FCS: Feature Calibration and Separation for Non-Exemplar Class Incremental Learning
CVPR 2024
FD3D: Exploiting Foreground Depth Map for Feature-Supervised Monocular 3D Object Detection
AAAI 2024
Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation
MIDL 2024
Feasibility Consistent Representation Learning for Safe Reinforcement Learning
ICML 2024
Feature Contamination: Neural Networks Learn Uncorrelated Features and Fail to Generalize
ICML 2024
Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathology
CVPR 2024
Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models
ICML 2024