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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)

FAKD: Feature Augmented Knowledge Distillation for Semantic Segmentation WACV 2024 FakeSound: Deepfake General Audio Detection Interspeech 2024 FAME: Towards Factual Multi-Task Model Editing EMNLP 2024 FanLoRA: Fantastic LoRAs and Where to Find Them in Large Language Model Fine-tuning EMNLP 2024 FashionERN: Enhance-and-Refine Network for Composed Fashion Image Retrieval AAAI 2024 Fast Adaptation for Human Pose Estimation via Meta-Optimization CVPR 2024 FastAdaSP: Multitask-Adapted Efficient Inference for Large Speech Language Model EMNLP 2024 Fast and Knowledge-Free Deep Learning for General Game Playing (Student Abstract) AAAI 2024 Fast Best-of-N Decoding via Speculative Rejection NeurIPS 2024 FastCLIPstyler: Optimisation-Free Text-Based Image Style Transfer Using Style Representations WACV 2024 Fast Context-Based Low-Light Image Enhancement via Neural Implicit Representations ECCV 2024 Faster Neighborhood Attention: Reducing the O(n^2) Cost of Self Attention at the Threadblock Level NeurIPS 2024 FastGAS: Fast Graph-based Annotation Selection for In-Context Learning ACL 2024 Fast Imitation via Behavior Foundation Models ICLR 2024 Fast Inter-frame Motion Prediction for Compressed Dynamic Point Cloud Attribute Enhancement AAAI 2024 FASTopic: Pretrained Transformer is a Fast, Adaptive, Stable, and Transferable Topic Model NeurIPS 2024 Fast Randomized Low-Rank Adaptation of Pre-trained Language Models with PAC Regularization ACL 2024 Fast Streaming Transducer ASR Prototyping via Knowledge Distillation with Whisper EMNLP 2024 FCS: Feature Calibration and Separation for Non-Exemplar Class Incremental Learning CVPR 2024 FD3D: Exploiting Foreground Depth Map for Feature-Supervised Monocular 3D Object Detection AAAI 2024 Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation MIDL 2024 Feasibility Consistent Representation Learning for Safe Reinforcement Learning ICML 2024 Feature Contamination: Neural Networks Learn Uncorrelated Features and Fail to Generalize ICML 2024 Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathology CVPR 2024 Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models ICML 2024