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)
Accelerating Diffusion Models for Inverse Problems through Shortcut Sampling
IJCAI 2024
Accelerating Pre-training of Multimodal LLMs via Chain-of-Sight
NeurIPS 2024
AccentFold: A Journey through African Accents for Zero-Shot ASR Adaptation to Target Accents
EACL 2024
ACCEPT: Adaptive Codebook for Composite and Efficient Prompt Tuning
EMNLP 2024
Accept the Modality Gap: An Exploration in the Hyperbolic Space
CVPR 2024
Accurate and Data-Efficient Toxicity Prediction when Annotators Disagree
EMNLP 2024
Accurate and Steady Inertial Pose Estimation through Sequence Structure Learning and Modulation
NeurIPS 2024
Accurate Forgetting for Heterogeneous Federated Continual Learning
ICLR 2024
ACES: Generating a Diversity of Challenging Programming Puzzles with Autotelic Generative Models
NeurIPS 2024
A Chain-of-Thought Prompting Approach with LLMs for Evaluating Students’ Formative Assessment Responses in Science
AAAI 2024
Achievable distributional robustness when the robust risk is only partially identified
NeurIPS 2024
Achieving Õ(1/ε) Sample Complexity for Constrained Markov Decision Process
NeurIPS 2024
Achieving Domain-Independent Certified Robustness via Knowledge Continuity
NeurIPS 2024
Achieving Fairness through Separability: A Unified Framework for Fair Representation Learning
AISTATS 2024
Achieving Group Distributional Robustness and Minimax Group Fairness with Interpolating Classifiers
AISTATS 2024
Achieving Human Parity in Content-Grounded Datasets Generation
ICLR 2024
Achieving Stronger Generation via Simple Contrastive Tuning
EMNLP 2024
Achieving Tractable Minimax Optimal Regret in Average Reward MDPs
NeurIPS 2024
Achilles-Bench: A Challenging Benchmark for Low-Resource Evaluation
ACL 2024
A Classification-Guided Approach for Adversarial Attacks against Neural Machine Translation
EACL 2024
A Closer Look at Claim Decomposition
NAACL 2024
A Closer Look at Curriculum Adversarial Training: From an Online Perspective
AAAI 2024
A Closer Look at the CLS Token for Cross-Domain Few-Shot Learning
NeurIPS 2024
A Closer Look at the Limitations of Instruction Tuning
ICML 2024
A Coarse-to-Fine Prototype Learning Approach for Multi-Label Few-Shot Intent Detection
EMNLP 2024