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Learning Types

32,670 papers (1 classified directly here)

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)
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Papers (including subtopics)

Deep Neural Room Acoustics Primitive ICML 2024 DeepPavlov 1.0: Your Gateway to Advanced NLP Models Backed by Transformers and Transfer Learning EMNLP 2024 Deep Regression Representation Learning with Topology ICML 2024 Deep Reinforcement Learning for Communication Networks AAAI 2024 DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routing AAAI 2024 DeepStack: Deeply Stacking Visual Tokens is Surprisingly Simple and Effective for LMMs NeurIPS 2024 Deep Unfolded Network with Intrinsic Supervision for Pan-Sharpening AAAI 2024 Deep Video Inverse Tone Mapping Based on Temporal Clues CVPR 2024 Deep Visual-Genetic Biometrics for Taxonomic Classification of Rare Species WACV 2024 DeeR-VLA: Dynamic Inference of Multimodal Large Language Models for Efficient Robot Execution NeurIPS 2024 Defending Jailbreak Prompts via In-Context Adversarial Game EMNLP 2024 Defending Large Language Models Against Jailbreak Attacks via Layer-specific Editing EMNLP 2024 Defending Object Detection Models Against Image Distortions WACV 2024 Defense Against Adversarial Attacks on No-Reference Image Quality Models with Gradient Norm Regularization CVPR 2024 Defense without Forgetting: Continual Adversarial Defense with Anisotropic & Isotropic Pseudo Replay CVPR 2024 Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models NeurIPS 2024 Defog Artificial Intelligence Glasses: Neural Networks for the Imperfect Real World AAAI 2024 DeformableTST: Transformer for Time Series Forecasting without Over-reliance on Patching NeurIPS 2024 DEFT: Efficient Fine-tuning of Diffusion Models by Learning the Generalised h-transform NeurIPS 2024 DeiT-LT: Distillation Strikes Back for Vision Transformer Training on Long-Tailed Datasets CVPR 2024 Déjà Vu Memorization in Vision–Language Models NeurIPS 2024 Delving into Qualitative Implications of Synthetic Data for Hate Speech Detection EMNLP 2024 Delving into the Trajectory Long-tail Distribution for Muti-object Tracking CVPR 2024 DeMatch: Deep Decomposition of Motion Field for Two-View Correspondence Learning CVPR 2024 DEM: Distribution Edited Model for Training with Mixed Data Distributions EMNLP 2024