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
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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)
Retrieved Sequence Augmentation for Protein Representation Learning
EMNLP 2024
Retrieve-Plan-Generation: An Iterative Planning and Answering Framework for Knowledge-Intensive LLM Generation
EMNLP 2024
Retrieving Contextual Information for Long-Form Question Answering using Weak Supervision
EMNLP 2024
Retrieving Examples from Memory for Retrieval Augmented Neural Machine Translation: A Systematic Comparison
NAACL 2024
Retrieving Semantics for Fact-Checking: A Comparative Approach using CQ (Claim to Question) & AQ (Answer to Question)
EMNLP 2024
RetroOOD: Understanding Out-of-Distribution Generalization in Retrosynthesis Prediction
AAAI 2024
Re-Tuning: Overcoming the Compositionality Limits of Large Language Models with Recursive Tuning
ACL 2024
Return of Unconditional Generation: A Self-supervised Representation Generation Method
NeurIPS 2024
Reuse Your Rewards: Reward Model Transfer for Zero-Shot Cross-Lingual Alignment
EMNLP 2024
Reusing Transferable Weight Increments for Low-resource Style Generation
EMNLP 2024
REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes
ICLR 2024
Revealing Distribution Discrepancy by Sampling Transfer in Unlabeled Data
NeurIPS 2024
Revealing Hierarchical Structure of Leaf Venations in Plant Science via Label-Efficient Segmentation: Dataset and Method
IJCAI 2024
Revealing the Proximate Long-Tail Distribution in Compositional Zero-Shot Learning
AAAI 2024
Revealing the Two Sides of Data Augmentation: An Asymmetric Distillation-based Win-Win Solution for Open-Set Recognition
IJCAI 2024
Reverse-Engineering the Reader
EMNLP 2024
Reverse Knowledge Distillation: Training a Large Model Using a Small One for Retinal Image Matching on Limited Data
WACV 2024
Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference
NeurIPS 2024
Review-Enhanced Hierarchical Contrastive Learning for Recommendation
AAAI 2024
Reviewing the Forgotten Classes for Domain Adaptation of Black-Box Predictors
AAAI 2024
Revisiting Adversarial Patches for Designing Camera-Agnostic Attacks against Person Detection
NeurIPS 2024
Revisiting Adversarial Training at Scale
CVPR 2024
Revisiting Adversarial Training Under Long-Tailed Distributions
CVPR 2024
Revisiting, Benchmarking and Understanding Unsupervised Graph Domain Adaptation
NeurIPS 2024
Revisiting Catastrophic Forgetting in Large Language Model Tuning
EMNLP 2024