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)
What Do Language Models Learn in Context? The Structured Task Hypothesis.
ACL 2024
What do Large Language Models Need for Machine Translation Evaluation?
EMNLP 2024
whatdoyoumeme at SemEval-2024 Task 4: Hierarchical-Label-Aware Persuasion Detection using Translated Texts
SemEval 2024
What happens in continued pre-training? Analysis of self-supervised speech models with continued pre-training for colloquial Finnish ASR
Interspeech 2024
What How and When Should Object Detectors Update in Continually Changing Test Domains?
CVPR 2024
What if...?: Thinking Counterfactual Keywords Helps to Mitigate Hallucination in Large Multi-modal Models
EMNLP 2024
What is lost in Normalization? Exploring Pitfalls in Multilingual ASR Model Evaluations
EMNLP 2024
What is the Best Way for ChatGPT to Translate Poetry?
ACL 2024
“What is the value of templates?” Rethinking Document Information Extraction Datasets for LLMs
EMNLP 2024
What is “Typological Diversity” in NLP?
EMNLP 2024
What Kind of Sourcery is This? Evaluating GPT-4’s Performance on Linking Scientific Fact to Citations
EMNLP 2024
What Makes a Good Order of Examples in In-Context Learning
ACL 2024
What Makes and Breaks Safety Fine-tuning? A Mechanistic Study
NeurIPS 2024
What Makes CLIP More Robust to Long-Tailed Pre-Training Data? A Controlled Study for Transferable Insights
NeurIPS 2024
What Makes Good Collaborative Views? Contrastive Mutual Information Maximization for Multi-Agent Perception
AAAI 2024
What Makes Partial-Label Learning Algorithms Effective?
NeurIPS 2024
What Matters in Graph Class Incremental Learning? An Information Preservation Perspective
NeurIPS 2024
What Matters in Memorizing and Recalling Facts? Multifaceted Benchmarks for Knowledge Probing in Language Models
EMNLP 2024
What Rotary Position Embedding Can Tell Us: Identifying Query and Key Weights Corresponding to Basic Syntactic or High-level Semantic Information
NeurIPS 2024
What's in the Flow? Exploiting Temporal Motion Cues for Unsupervised Generic Event Boundary Detection
WACV 2024
What's Outside the Intersection? Fine-Grained Error Analysis for Semantic Segmentation Beyond IoU
WACV 2024
What the Weight?! A Unified Framework for Zero-Shot Knowledge Composition
EACL 2024
What to Annotate: Retrieving Lexical Markers of Conspiracy Discourse from an Italian-English Corpus of Telegram Data
COLING 2024
What to Remember: Self-Adaptive Continual Learning for Audio Deepfake Detection
AAAI 2024
What to Say and When to Say it: Live Fitness Coaching as a Testbed for Situated Interaction
NeurIPS 2024