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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)

Two-Stage Evolutionary Reinforcement Learning for Enhancing Exploration and Exploitation AAAI 2024 Two Tales of Single-Phase Contrastive Hebbian Learning ICML 2024 Typos that Broke the RAG’s Back: Genetic Attack on RAG Pipeline by Simulating Documents in the Wild via Low-level Perturbations EMNLP 2024 UDA: A Benchmark Suite for Retrieval Augmented Generation in Real-World Document Analysis NeurIPS 2024 UDON: Universal Dynamic Online distillatioN for generic image representations NeurIPS 2024 UDPM: Upsampling Diffusion Probabilistic Models NeurIPS 2024 UFCNet: Unsupervised Network based on Fourier transform and Convolutional attention for Oracle Character Recognition ACL 2024 UFORecon: Generalizable Sparse-View Surface Reconstruction from Arbitrary and Unfavorable Sets CVPR 2024 UltraLink: An Open-Source Knowledge-Enhanced Multilingual Supervised Fine-tuning Dataset ACL 2024 UltraSparseBERT: 99% Conditionally Sparse Language Modelling ACL 2024 UMA: Facilitating Backdoor Scanning via Unlearning-Based Model Ablation AAAI 2024 UMB: Understanding Model Behavior for Open-World Object Detection NeurIPS 2024 Unbiased Faster R-CNN for Single-source Domain Generalized Object Detection CVPR 2024 Unbiased Multi-Label Learning from Crowdsourced Annotations ICML 2024 Uncertainty-aware Action Decoupling Transformer for Action Anticipation CVPR 2024 Uncertainty-aware Fine-tuning of Segmentation Foundation Models NeurIPS 2024 Uncertainty-Aware GAN for Single Image Super Resolution AAAI 2024 Uncertainty-Aware Yield Prediction with Multimodal Molecular Features AAAI 2024 Uncertainty Estimation in Instance Segmentation With Star-Convex Shapes WACV 2024 Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor Defense NeurIPS 2024 Understanding Addition in Transformers ICLR 2024 Understanding Bias in Large-Scale Visual Datasets NeurIPS 2024 Understanding Dark Scenes by Contrasting Multi-Modal Observations WACV 2024 Understanding Distributed Representations of Concepts in Deep Neural Networks without Supervision AAAI 2024 Understanding Generalizability of Diffusion Models Requires Rethinking the Hidden Gaussian Structure NeurIPS 2024