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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)

Parallel Backpropagation for Shared-Feature Visualization NeurIPS 2024 Parallel Structures in Pre-training Data Yield In-Context Learning ACL 2024 Parameter Efficient Fine-tuning via Cross Block Orchestration for Segment Anything Model CVPR 2024 Parameter-Efficient Fine-Tuning with Discrete Fourier Transform ICML 2024 Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization ICLR 2024 Parameter Efficient Self-Supervised Geospatial Domain Adaptation CVPR 2024 ParamISP: Learned Forward and Inverse ISPs using Camera Parameters CVPR 2024 PARA: Parameter-Efficient Fine-tuning with Prompt-Aware Representation Adjustment EMNLP 2024 PARSAC: Accelerating Robust Multi-Model Fitting with Parallel Sample Consensus AAAI 2024 Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting NeurIPS 2024 Part-aware Unified Representation of Language and Skeleton for Zero-shot Action Recognition CVPR 2024 PartDistill: 3D Shape Part Segmentation by Vision-Language Model Distillation CVPR 2024 Partial Multi-View Multi-Label Classification via Semantic Invariance Learning and Prototype Modeling ICML 2024 Patch2Self2: Self-supervised Denoising on Coresets via Matrix Sketching CVPR 2024 patchDPCC: A Patchwise Deep Compression Framework for Dynamic Point Clouds AAAI 2024 Patched Line Segment Learning for Vector Road Mapping AAAI 2024 PatchFusion: An End-to-End Tile-Based Framework for High-Resolution Monocular Metric Depth Estimation CVPR 2024 Patentformer: A Novel Method to Automate the Generation of Patent Applications EMNLP 2024 PathAsst: A Generative Foundation AI Assistant towards Artificial General Intelligence of Pathology AAAI 2024 Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting ICLR 2024 Pcc-tuning: Breaking the Contrastive Learning Ceiling in Semantic Textual Similarity EMNLP 2024 PCP-MAE: Learning to Predict Centers for Point Masked Autoencoders NeurIPS 2024 PDF: A Probability-Driven Framework for Open World 3D Point Cloud Semantic Segmentation CVPR 2024 PDFTriage: Question Answering over Long, Structured Documents EMNLP 2024 PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming ICML 2024