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
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Papers (including subtopics)
Improved Self-Training for Test-Time Adaptation
CVPR 2024
Improved Visual Grounding through Self-Consistent Explanations
CVPR 2024
Improved Zero-Shot Classification by Adapting VLMs with Text Descriptions
CVPR 2024
Improve Meta-learning for Few-Shot Text Classification with All You Can Acquire from the Tasks
EMNLP 2024
Improve Robustness of Reinforcement Learning against Observation Perturbations via l∞ Lipschitz Policy Networks
AAAI 2024
Improving Acoustic Word Embeddings through Correspondence Training of Self-supervised Speech Representations
EACL 2024
Improving Adversarial Data Collection by Supporting Annotators: Lessons from GAHD, a German Hate Speech Dataset
NAACL 2024
Improving Adversarial Robustness in Vision-Language Models with Architecture and Prompt Design
EMNLP 2024
Improving Adversarial Robustness via Feature Pattern Consistency Constraint
IJCAI 2024
Improving Argument Effectiveness Across Ideologies using Instruction-tuned Large Language Models
EMNLP 2024
Improving Attributed Text Generation of Large Language Models via Preference Learning
ACL 2024
Improving Audio Classification with Low-Sampled Microphone Input: An Empirical Study Using Model Self-Distillation
Interspeech 2024
Improving Content Recommendation: Knowledge Graph-Based Semantic Contrastive Learning for Diversity and Cold-Start Users
COLING 2024
Improving Context-Aware Preference Modeling for Language Models
NeurIPS 2024
Improving Continual Few-shot Relation Extraction through Relational Knowledge Distillation and Prototype Augmentation
COLING 2024
Improving Contrastive Learning in Emotion Recognition in Conversation via Data Augmentation and Decoupled Neutral Emotion
EACL 2024
Improving Covert Toxicity Detection by Retrieving and Generating References
NAACL 2024
Improving Cross-lingual Transfer with Contrastive Negative Learning and Self-training
COLING 2024
Improving Decision Sparsity
NeurIPS 2024
Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn
NeurIPS 2024
Improving Demonstration Diversity by Human-Free Fusing for Text-to-SQL
EMNLP 2024
Improving Dialog Safety using Socially Aware Contrastive Learning
EACL 2024
Improving Discriminative Capability of Reward Models in RLHF Using Contrastive Learning
EMNLP 2024
Improving Event Definition Following For Zero-Shot Event Detection
ACL 2024
Improving Factual Consistency of News Summarization by Contrastive Preference Optimization
EMNLP 2024