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Learning Types

32,670 papers (1 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Representation Learning (5,307) Multimodal Learning (3,969) Self-Supervised Learning (3,492) Transfer Learning (2,890) Adversarial Learning (2,199) Deep Learning (1,883) Contrastive Learning (1,730) Reinforcement Learning (1,500) Knowledge Distillation (1,494) Fine-Tuning (1,117) Multi-Task Learning (1,069) Domain Adaptation (977) Zero-Shot Learning (758) Unsupervised Learning (734) Few-Shot Learning (694) Classification (621) Retrieval-Augmented Generation (606) Data Augmentation (583) Semi-Supervised Learning (450) Weakly Supervised Learning (429) Continual Learning (408) In-Context Learning (387) Sequence Modeling (375) Meta-Learning (252) Metric Learning (232) Ensemble Learning (223) Federated Learning (215) Multi-Lingual Learning (199) Robustness (197) Parameter-Efficient Fine-Tuning (190) Imitation Learning (180) Prompt Engineering (170) Chain-of-Thought Reasoning (153) Curriculum Learning (146) Synthetic Data Generation (143) Reinforcement Learning from Human Feedback (141) Multi-Label Classification (123) Regression (117) Generative Model (109) Semantic Segmentation (106) Domain Generalization (105) Uncertainty Quantification (98) Controllable Generation (93) Text Generation (86) Neural Architecture Search (80) Object Detection (80) Image Generation (79) Multi-Agent Systems (76) Feature Learning (74) Preference Learning (73) Machine Translation (71) Out-of-Distribution Detection (68) Machine Unlearning (63) Generation (61) Reasoning (54) Multi-View Learning (53) Time Series (52) Instruction Tuning (50) Distributed Learning (50) Image Restoration (49) Chain-of-Thought (48) Active Learning (47) Text Classification (43) Distribution Shift (43) Structured Prediction (42) Clustering (41) Image Classification (40) Model Merging (37) Sparse Learning (36) Sequence Labeling (36) Multi-Instance Learning (35) Anomaly Detection (33) Image Processing (33) Code Generation (31) Fairness (30) Robust Learning (28) Multi-Domain Learning (27) Supervised Learning (26) Model-Based RL (25) Natural Language Generation (24) Privacy (21) Multi-Objective Optimization (19) Multi-Scale Learning (19) Neural Machine Translation (18) Causal Inference (14) Instance Segmentation (9) Interactive Learning (9) Multi-Label Learning (9) Multi-Source Learning (9) Multi-Class Classification (8)

Papers per year

38
179
3,018
5,737
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'15
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'25

Papers (including subtopics)

CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison AAAI 2019 ClariNet: Parallel Wave Generation in End-to-End Text-to-Speech ICLR 2019 Class-Balanced Loss Based on Effective Number of Samples CVPR 2019 Classification-Reconstruction Learning for Open-Set Recognition CVPR 2019 CLEVR-Ref+: Diagnosing Visual Reasoning With Referring Expressions CVPR 2019 Clickbait? Sensational Headline Generation with Auto-tuned Reinforcement Learning EMNLP 2019 Cloze-driven Pretraining of Self-attention Networks EMNLP 2019 ClusterGAN: Latent Space Clustering in Generative Adversarial Networks AAAI 2019 CM-Net: A Novel Collaborative Memory Network for Spoken Language Understanding EMNLP 2019 CNNs found to jump around more skillfully than RNNs: Compositional Generalization in Seq2seq Convolutional Networks ACL 2019 code2seq: Generating Sequences from Structured Representations of Code ICLR 2019 Code Generation as a Dual Task of Code Summarization NeurIPS 2019 CoDraw: Collaborative Drawing as a Testbed for Grounded Goal-driven Communication ACL 2019 Cognitive Deficit of Deep Learning in Numerosity AAAI 2019 Collaborative Learning of Semi-Supervised Segmentation and Classification for Medical Images CVPR 2019 Collaborative Policy Learning for Open Knowledge Graph Reasoning EMNLP 2019 CollaGAN: Collaborative GAN for Missing Image Data Imputation CVPR 2019 Coloring With Limited Data: Few-Shot Colorization via Memory Augmented Networks CVPR 2019 Combined Reinforcement Learning via Abstract Representations AAAI 2019 Combining Deep Learning and Qualitative Spatial Reasoning to Learn Complex Structures from Sparse Examples with Noise AAAI 2019 Combining Deep Learning and Verification for Precise Object Instance Detection CoRL 2019 Combining Fact Extraction and Verification with Neural Semantic Matching Networks AAAI 2019 Combining Global Sparse Gradients with Local Gradients in Distributed Neural Network Training EMNLP 2019 Combining Unsupervised Pre-training and Annotator Rationales to Improve Low-shot Text Classification EMNLP 2019 ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples CVPR 2019