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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)

Evidential Uncertainty-Guided Mitochondria Segmentation for 3D EM Images AAAI 2024 EVIT: Event-Oriented Instruction Tuning for Event Reasoning ACL 2024 Evolutionary Contrastive Distillation for Language Model Alignment EMNLP 2024 Evolution-Inspired Loss Functions for Protein Representation Learning ICML 2024 EvoR: Evolving Retrieval for Code Generation EMNLP 2024 EVS-assisted Joint Deblurring Rolling-Shutter Correction and Video Frame Interpolation through Sensor Inverse Modeling CVPR 2024 EvTexture: Event-driven Texture Enhancement for Video Super-Resolution ICML 2024 ExACT: Language-guided Conceptual Reasoning and Uncertainty Estimation for Event-based Action Recognition and More CVPR 2024 EXAMS-V: A Multi-Discipline Multilingual Multimodal Exam Benchmark for Evaluating Vision Language Models ACL 2024 ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis ICLR 2024 Existence and Minimax Theorems for Adversarial Surrogate Risks in Binary Classification JMLR 2024 Existence Is Chaos: Enhancing 3D Human Motion Prediction with Uncertainty Consideration AAAI 2024 ExMap: Leveraging Explainability Heatmaps for Unsupervised Group Robustness to Spurious Correlations CVPR 2024 ExMatch: Self-guided Exploitation for Semi-Supervised Learning with Scarce Labeled Samples ECCV 2024 Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning CVPR 2024 Expanding Expressiveness of Diffusion Models With Limited Data via Self-Distillation Based Fine-Tuning WACV 2024 Expected flow networks in stochastic environments and two-player zero-sum games ICLR 2024 Expediting Contrastive Language-Image Pretraining via Self-Distilled Encoders AAAI 2024 Experiential Co-Learning of Software-Developing Agents ACL 2024 Experimental Contexts Can Facilitate Robust Semantic Property Inference in Language Models, but Inconsistently EMNLP 2024 Explainable Earnings Call Representation Learning (Student Abstract) AAAI 2024 Explaining and Improving Contrastive Decoding by Extrapolating the Probabilities of a Huge and Hypothetical LM EMNLP 2024 Explaining CLIP's Performance Disparities on Data from Blind/Low Vision Users CVPR 2024 Explaining the Implicit Neural Canvas: Connecting Pixels to Neurons by Tracing their Contributions CVPR 2024 Explanation-aware Soft Ensemble Empowers Large Language Model In-context Learning ACL 2024