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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
'10
'15
'20
'25

Papers (including subtopics)

ProphNet: Efficient Agent-Centric Motion Forecasting With Anchor-Informed Proposals CVPR 2023 Proposal-Based Multiple Instance Learning for Weakly-Supervised Temporal Action Localization CVPR 2023 PropSegmEnt: A Large-Scale Corpus for Proposition-Level Segmentation and Entailment Recognition ACL 2023 Prosody-TTS: Improving Prosody with Masked Autoencoder and Conditional Diffusion Model For Expressive Text-to-Speech ACL 2023 ProTeGe: Untrimmed Pretraining for Video Temporal Grounding by Video Temporal Grounding CVPR 2023 ProteinNPT: Improving Protein Property Prediction and Design with Non-Parametric Transformers NeurIPS 2023 ProtoCon: Pseudo-Label Refinement via Online Clustering and Prototypical Consistency for Efficient Semi-Supervised Learning CVPR 2023 ProtoDiffusion: Classifier-Free Diffusion Guidance with Prototype Learning ACML 2023 Proto-lm: A Prototypical Network-Based Framework for Built-in Interpretability in Large Language Models EMNLP 2023 Prototype-based Aleatoric Uncertainty Quantification for Cross-modal Retrieval NeurIPS 2023 Prototype-based HyperAdapter for Sample-Efficient Multi-task Tuning EMNLP 2023 Prototype-Sample Relation Distillation: Towards Replay-Free Continual Learning ICML 2023 Prototypical Fine-Tuning: Towards Robust Performance under Varying Data Sizes AAAI 2023 Prototypical Model with Information-Theoretic Loss Functions for Generalized Zero-Shot Learning ACML 2023 Prototypical Partial Optimal Transport for Universal Domain Adaptation AAAI 2023 Provable Advantage of Curriculum Learning on Parity Targets with Mixed Inputs NeurIPS 2023 Provable Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More NeurIPS 2023 Provable Benefits of Representational Transfer in Reinforcement Learning COLT 2023 Provable Dynamic Fusion for Low-Quality Multimodal Data ICML 2023 Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior NeurIPS 2023 Provable Pathways: Learning Multiple Tasks over Multiple Paths AAAI 2023 Proximal Splitting Adversarial Attack for Semantic Segmentation CVPR 2023 ProxyFormer: Proxy Alignment Assisted Point Cloud Completion With Missing Part Sensitive Transformer CVPR 2023 Pseudo-Label Guided Contrastive Learning for Semi-Supervised Medical Image Segmentation CVPR 2023 Pseudo Label-Guided Model Inversion Attack via Conditional Generative Adversarial Network AAAI 2023