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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)

MoDE: A Mixture-of-Experts Model with Mutual Distillation among the Experts AAAI 2024 MoDE: CLIP Data Experts via Clustering CVPR 2024 MoDE-CoTD: Chain-of-Thought Distillation for Complex Reasoning Tasks with Mixture of Decoupled LoRA-Experts COLING 2024 Model Adaptation for Time Constrained Embodied Control CVPR 2024 Model-based Diffusion for Trajectory Optimization NeurIPS 2024 Model Based Inference of Synaptic Plasticity Rules NeurIPS 2024 Model-based Preference Optimization in Abstractive Summarization without Human Feedback EMNLP 2024 Model Editing by Standard Fine-Tuning ACL 2024 Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue EMNLP 2024 Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation NeurIPS 2024 Model-Free Representation Learning and Exploration in Low-Rank MDPs JMLR 2024 Modeling Collaborator: Enabling Subjective Vision Classification With Minimal Human Effort via LLM Tool-Use CVPR 2024 Modeling Complex Interactions in Long Documents for Aspect-Based Sentiment Analysis ACL 2024 Modeling Dynamic Topics in Chain-Free Fashion by Evolution-Tracking Contrastive Learning and Unassociated Word Exclusion ACL 2024 Modeling Uncertainty and Using Post-fusion as Fallback Improves Retrieval Augmented Generation with LLMs ACL 2024 Modeling User Preferences with Automatic Metrics: Creating a High-Quality Preference Dataset for Machine Translation EMNLP 2024 Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented Generation EMNLP 2024 Modelling Commonsense Commonalities with Multi-Facet Concept Embeddings ACL 2024 Model Reprogramming: Resource-Efficient Cross-Domain Machine Learning AAAI 2024 Moderate Message Passing Improves Calibration: A Universal Way to Mitigate Confidence Bias in Graph Neural Networks AAAI 2024 ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis ICLR 2024 MoDULA: Mixture of Domain-Specific and Universal LoRA for Multi-Task Learning EMNLP 2024 Modular Adaptation of Multilingual Encoders to Written Swiss German Dialect EACL 2024 Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration EMNLP 2024 MoE Jetpack: From Dense Checkpoints to Adaptive Mixture of Experts for Vision Tasks NeurIPS 2024