Learning Types
56,253 papers (3 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Self-Supervised Learning (8,965)
Adversarial Learning (5,204)
Unsupervised Learning (4,874)
Transfer Learning (4,808)
Weakly Supervised Learning (3,938)
Contrastive Learning (3,748)
Zero-Shot Learning (3,130)
Semi-Supervised Learning (3,128)
Reinforcement Learning (3,118)
Multi-Task Learning (2,556)
Evaluation (2,164)
Continual Learning (2,107)
Active Learning (1,983)
Few-Shot Learning (1,840)
Deep Learning (1,404)
Online Learning (1,360)
Multi-Armed Bandits (1,327)
Multimodal Learning (1,289)
Supervised Learning (986)
Multi-Agent Systems (813)
Uncertainty Quantification (805)
Causal Inference (636)
Robustness (576)
Retrieval-Augmented Generation (565)
Fine-Tuning (490)
Ensemble Learning (482)
In-Context Learning (439)
Multi-Label Classification (430)
Imitation Learning (387)
Prompt Engineering (270)
Multi-Lingual Learning (269)
Distribution Shift (264)
Reinforcement Learning from Human Feedback (209)
Regularization (207)
Exploration-Exploitation (203)
Generative Models (200)
Multi-Objective Optimization (185)
Out-of-Distribution Detection (176)
Sparse Learning (165)
Sampling (150)
Preference Learning (136)
Offline Reinforcement Learning (130)
Multi-Label Learning (128)
Markov Decision Process (127)
Neural Architecture Search (122)
Multi-Instance Learning (121)
Multi-View Learning (117)
Robust Learning (110)
Generative Model (110)
Time Series (108)
Large Language Models (104)
Exploration (103)
Hyperparameter Optimization (99)
Machine Unlearning (95)
Imbalanced Learning (93)
Machine Translation (93)
Multi-Class Classification (85)
Differential Privacy (82)
Time Series Analysis (71)
Reasoning (70)
Calibration (67)
Structure Learning (66)
Physics-Informed Learning (62)
Class Imbalance (58)
Model-Based RL (55)
Interactive Learning (55)
Multi-Domain Learning (47)
Inverse Reinforcement Learning (46)
Crowdsourcing (40)
Off-Policy Learning (38)
Label Noise (38)
Noisy Label Learning (35)
Offline RL (32)
Attention (32)
Evolutionary Algorithm (32)
Decision Making (31)
Policy Learning (30)
Personalization (28)
Low-Resource Learning (26)
Collaborative Filtering (25)
Self-Training (24)
Sequential Modeling (24)
Parameter Estimation (23)
Survival Analysis (21)
Machine Learning (20)
Parameter-Efficient Fine-Tuning (20)
Synthetic Data Generation (20)
Annotation (18)
Symbolic Regression (18)
AutoML (16)
Security (15)
Multi-Source Learning (13)
Distant Supervision (13)
Text Generation (11)
Distributional Reinforcement Learning (9)
Sentiment Analysis (9)
Multi-Hop Reasoning (9)
Language Modeling (9)
Code Generation (8)
Multi-Object Tracking (8)
Natural Language Inference (7)
Chain-of-Thought (6)
Question Answering (5)
Papers per year
1
8
12
26
18
20
135
136
147
149
220
231
316
526
460
477
660
1,314
2,083
3,689
4,652
5,914
6,826
8,201
8,755
9,258
2,019
2000
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'20
'25
Papers (including subtopics)
Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning
IJCAI 2024
Towards Safe Policy Learning under Partial Identifiability: A Causal Approach
AAAI 2024
Towards Safer Large Language Models through Machine Unlearning
ACL 2024
Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network
CVPR 2024
Towards Sharper Generalization Bounds for Adversarial Contrastive Learning
IJCAI 2024
Towards Stable Representations for Protein Interface Prediction
NeurIPS 2024
Towards Supervised Performance on Speaker Verification with Self-Supervised Learning by Leveraging Large-Scale ASR Models
Interspeech 2024
Towards Surveillance Video-and-Language Understanding: New Dataset Baselines and Challenges
CVPR 2024
Towards the Robustness of Differentially Private Federated Learning
AAAI 2024
Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms
ICML 2024
Towards the Transferability of Rewards Recovered via Regularized Inverse Reinforcement Learning
NeurIPS 2024
Towards the Uncharted: Density-Descending Feature Perturbation for Semi-supervised Semantic Segmentation
CVPR 2024
Towards Tool Use Alignment of Large Language Models
EMNLP 2024
Towards training digitally-tied analog blocks via hybrid gradient computation
NeurIPS 2024
Towards Transferable Adversarial Attacks with Centralized Perturbation
AAAI 2024
Towards Transferable Targeted 3D Adversarial Attack in the Physical World
CVPR 2024
Towards Transparent Time Series Forecasting
ICLR 2024
Towards Trustworthy Deep Learning
AAAI 2024
Towards Unbiased Exploration in Partial Label Learning
JMLR 2024
Towards Uncertainty-Aware Language Agent
ACL 2024
Towards Understanding and Improving Adversarial Robustness of Vision Transformers
CVPR 2024
Towards Understanding Counseling Conversations: Domain Knowledge and Large Language Models
EACL 2024
Towards Understanding the Relationship between In-context Learning and Compositional Generalization
COLING 2024
Towards Unified Task Embeddings Across Multiple Models: Bridging the Gap for Prompt-Based Large Language Models and Beyond
ACL 2024
Towards Unsupervised Model Selection for Domain Adaptive Object Detection
NeurIPS 2024