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)
Q-Tuning: Queue-based Prompt Tuning for Lifelong Few-shot Language Learning
NAACL 2024
Quality-Aware Translation Models: Efficient Generation and Quality Estimation in a Single Model
ACL 2024
Quality-Diversity Generative Sampling for Learning with Synthetic Data
AAAI 2024
Quality-Diversity through AI Feedback
ICLR 2024
Quality Matters: Evaluating Synthetic Data for Tool-Using LLMs
EMNLP 2024
QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation
NeurIPS 2024
Quantifying Contamination in Evaluating Code Generation Capabilities of Language Models
ACL 2024
Quantifying Generalizations: Exploring the Divide Between Human and LLMs’ Sensitivity to Quantification
ACL 2024
Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting
ICLR 2024
Quantifying Local Model Validity using Active Learning
UAI 2024
Quantifying Representation Reliability in Self-Supervised Learning Models
UAI 2024
Quantifying the Gaps Between Translation and Native Perception in Training for Multimodal, Multilingual Retrieval
EMNLP 2024
Quantifying the Persona Effect in LLM Simulations
ACL 2024
Quantifying the Sensitivity of Inverse Reinforcement Learning to Misspecification
ICLR 2024
Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness
ACL 2024
Quantifying Uncertainty in Motion Prediction with Variational Bayesian Mixture
CVPR 2024
Quantifying Uncertainty in Natural Language Explanations of Large Language Models
AISTATS 2024
Quantile-Regression-Ensemble: A Deep Learning Algorithm for Downscaling Extreme Precipitation
AAAI 2024
QuantProb: Generalizing Probabilities along with Predictions for a Pre-trained Classifier
UAI 2024
Quantum Deep Equilibrium Models
NeurIPS 2024
Quantum Kernelized Bandits
UAI 2024
QuBE: Question-based Belief Enhancement for Agentic LLM Reasoning
EMNLP 2024
QueryAgent: A Reliable and Efficient Reasoning Framework with Environmental Feedback based Self-Correction
ACL 2024
Query-Based Adversarial Prompt Generation
NeurIPS 2024
Query-by-Example Keyword Spotting Using Spectral-Temporal Graph Attentive Pooling and Multi-Task Learning
Interspeech 2024