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)
Sleep-Like Unsupervised Replay Improves Performance When Data Are Limited or Unbalanced (Student Abstract)
AAAI 2024
Slice and Conquer: A Planar-to-3D Framework for Efficient Interactive Segmentation of Volumetric Images
WACV 2024
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method
ICLR 2024
SLIDE: A Framework Integrating Small and Large Language Models for Open-Domain Dialogues Evaluation
ACL 2024
SlideAVSR: A Dataset of Paper Explanation Videos for Audio-Visual Speech Recognition
ACL 2024
SLiMe: Segment Like Me
ICLR 2024
SLIM: Style-Linguistics Mismatch Model for Generalized Audio Deepfake Detection
NeurIPS 2024
Slot and Intent Detection Resources for Bavarian and Lithuanian: Assessing Translations vs Natural Queries to Digital Assistants
COLING 2024
SlowFormer: Adversarial Attack on Compute and Energy Consumption of Efficient Vision Transformers
CVPR 2024
SlowTrack: Increasing the Latency of Camera-Based Perception in Autonomous Driving Using Adversarial Examples
AAAI 2024
SM3-Text-to-Query: Synthetic Multi-Model Medical Text-to-Query Benchmark
NeurIPS 2024
Small coresets via negative dependence: DPPs, linear statistics, and concentration
NeurIPS 2024
Smaller Confidence Intervals From IPW Estimators via Data-Dependent Coarsening (Extended Abstract)
COLT 2024
Smaller Language Models are Better Zero-shot Machine-Generated Text Detectors
EACL 2024
Small Models are Valuable Plug-ins for Large Language Models
ACL 2024
Small Models, Big Insights: Leveraging Slim Proxy Models To Decide When and What to Retrieve for LLMs
ACL 2024
Small Objects Matters in Weakly-Supervised Semantic Segmentation
WACV 2024
Small steps no more: Global convergence of stochastic gradient bandits for arbitrary learning rates
NeurIPS 2024
SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models
NeurIPS 2024
SMARTCAL: An Approach to Self-Aware Tool-Use Evaluation and Calibration
EMNLP 2024
Smart Lexical Search for Label Flipping Adversial Attack
ACL 2024
SMART: Scalable Multi-agent Real-time Motion Generation via Next-token Prediction
NeurIPS 2024
SMART: Towards Pre-trained Missing-Aware Model for Patient Health Status Prediction
NeurIPS 2024
Sm: enhanced localization in Multiple Instance Learning for medical imaging classification
NeurIPS 2024
Smoke and Mirrors in Causal Downstream Tasks
NeurIPS 2024