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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Papers (including subtopics)
Distribution Learning with Valid Outputs Beyond the Worst-Case
NeurIPS 2024
Distribution Matching for Multi-Task Learning of Classification Tasks: A Large-Scale Study on Faces & Beyond
AAAI 2024
Dive into the Chasm: Probing the Gap between In- and Cross-Topic Generalization
EACL 2024
Diverse and Effective Synthetic Data Generation for Adaptable Zero-Shot Dialogue State Tracking
EMNLP 2024
Diverse Imagenet Models Transfer Better
WACV 2024
Diverse Yet Biased: Towards Mitigating Biases in Generative AI (Student Abstract)
AAAI 2024
Diversified and Personalized Multi-rater Medical Image Segmentation
CVPR 2024
Diversifying Training Pool Predictability for Zero-shot Coordination: A Theory of Mind Approach
IJCAI 2024
Diversify, Rationalize, and Combine: Ensembling Multiple QA Strategies for Zero-shot Knowledge-based VQA
EMNLP 2024
Diversity-Aware Annotation for Conversational AI Safety
COLING 2024
Diversity Is Not All You Need: Training A Robust Cooperative Agent Needs Specialist Partners
NeurIPS 2024
Diversity Over Size: On the Effect of Sample and Topic Sizes for Topic-Dependent Argument Mining Datasets
EMNLP 2024
Divide-and-Aggregate Learning for Evaluating Performance on Unlabeled Data
AAAI 2024
Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation
NeurIPS 2024
Divide and not forget: Ensemble of selectively trained experts in Continual Learning
ICLR 2024
Diving Segmentation Model into Pixels
ICLR 2024
DKEC: Domain Knowledge Enhanced Multi-Label Classification for Diagnosis Prediction
EMNLP 2024
DLM: A Decoupled Learning Model for Long-tailed Polyphone Disambiguation in Mandarin
NAACL 2024
DLUT and GTCOM’s Neural Machine Translation Systems for WMT24
EMNLP 2024
DM-BLI: Dynamic Multiple Subspaces Alignment for Unsupervised Bilingual Lexicon Induction
ACL 2024
DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors
NeurIPS 2024
DMMR: Cross-Subject Domain Generalization for EEG-Based Emotion Recognition via Denoising Mixed Mutual Reconstruction
AAAI 2024
DMoERM: Recipes of Mixture-of-Experts for Effective Reward Modeling
ACL 2024
DNA-GPT: Divergent N-Gram Analysis for Training-Free Detection of GPT-Generated Text
ICLR 2024
Do causal predictors generalize better to new domains?
NeurIPS 2024