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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)

Learning to Paraphrase for Alignment with LLM Preference EMNLP 2024 Learning to Pivot as a Smart Expert AAAI 2024 Learning to Rank in Generative Retrieval AAAI 2024 Learning to Rank Patches for Unbiased Image Redundancy Reduction CVPR 2024 Learning to Read Analog Gauges from Synthetic Data WACV 2024 Learning to Refine with Fine-Grained Natural Language Feedback EMNLP 2024 Learning to Rematch Mismatched Pairs for Robust Cross-Modal Retrieval CVPR 2024 Learning to Retrieve Iteratively for In-Context Learning EMNLP 2024 Learning to Segment Referred Objects from Narrated Egocentric Videos CVPR 2024 Learning to Shape In-distribution Feature Space for Out-of-distribution Detection NeurIPS 2024 Learning to Solve the Constrained Most Probable Explanation Task in Probabilistic Graphical Models AISTATS 2024 Learning to Trust Your Feelings: Leveraging Self-awareness in LLMs for Hallucination Mitigation ACL 2024 Learning to Visually Localize Sound Sources from Mixtures without Prior Source Knowledge CVPR 2024 Learning Transferable Features for Implicit Neural Representations NeurIPS 2024 Learning Transferable Negative Prompts for Out-of-Distribution Detection CVPR 2024 Learning Versatile Skills with Curriculum Masking NeurIPS 2024 Learning Vision from Models Rivals Learning Vision from Data CVPR 2024 Learning Visual Abstract Reasoning through Dual-Stream Networks AAAI 2024 Learning When to Retrieve, What to Rewrite, and How to Respond in Conversational QA EMNLP 2024 Learning with 3D rotations, a hitchhiker’s guide to SO(3) ICML 2024 Learning without Exact Guidance: Updating Large-scale High-resolution Land Cover Maps from Low-resolution Historical Labels CVPR 2024 Learning with Structural Labels for Learning with Noisy Labels CVPR 2024 Learning with Unreliability: Fast Few-shot Voxel Radiance Fields with Relative Geometric Consistency CVPR 2024 Learning World Models for Unconstrained Goal Navigation NeurIPS 2024 Learn it or Leave it: Module Composition and Pruning for Continual Learning ACL 2024