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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)

DeNVeR: Deformable Neural Vessel Representations for Unsupervised Video Vessel Segmentation CVPR 2025 Deploying Multi-task Online Server with Large Language Model COLING 2025 Deploying Tiny LVLM Judges for Real-World Evaluation of Chart Models: Lessons Learned and Best Practices EMNLP 2025 DepressGEN: Synthetic Data Generation Framework for Depression Detection Interspeech 2025 Depth Any Event Stream: Enhancing Event-based Monocular Depth Estimation via Dense-to-Sparse Distillation ICCV 2025 Derm1M: A Million-scale Vision-Language Dataset Aligned with Clinical Ontology Knowledge for Dermatology ICCV 2025 Describe Anything: Detailed Localized Image and Video Captioning ICCV 2025 DesignCLIP: Multimodal Learning with CLIP for Design Patent Understanding EMNLP 2025 Designing Specialized Two-Dimensional Graph Spectral Filters for Spatial-Temporal Graph Modeling AAAI 2025 DeSiRe-GS: 4D Street Gaussians for Static-Dynamic Decomposition and Surface Reconstruction for Urban Driving Scenes CVPR 2025 DeSPITE: Exploring Contrastive Deep Skeleton-Pointcloud-IMU-Text Embeddings for Advanced Point Cloud Human Activity Understanding ICCV 2025 Destroy and Repair Using Hyper-Graphs for Routing AAAI 2025 Details Enhancement in Unsigned Distance Field Learning for High-fidelity 3D Surface Reconstruction AAAI 2025 Detecting Adversarial Data Using Perturbation Forgery CVPR 2025 Detecting and Mitigating Challenges in Zero-Shot Video Summarization with Video LLMs ACL 2025 Detecting and Mitigating Hallucination in Large Vision Language Models via Fine-Grained AI Feedback AAAI 2025 Detecting Corpus-Level Knowledge Inconsistencies in Wikipedia with Large Language Models EMNLP 2025 Detecting Hallucination in Large Language Models Through Deep Internal Representation Analysis IJCAI 2025 Detecting Hallucinations in Scientific Claims by Combining Prompting Strategies and Internal State Classification ACL 2025 Detecting Honkadori based on Waka Embeddings NAACL 2025 Detecting Knowledge Boundary of Vision Large Language Models by Sampling-Based Inference EMNLP 2025 Detecting Music Performance Errors with Transformers AAAI 2025 Detoxifying Large Language Models via the Diversity of Toxic Samples EMNLP 2025 Developing a High-performance Framework for Speech Emotion Recognition in Naturalistic Conditions Challenge for Emotional Attribute Prediction Interspeech 2025 Developing a Top-tier Framework in Naturalistic Conditions Challenge for Categorized Emotion Prediction: From Speech Foundation Models and Learning Objective to Data Augmentation and Engineering Choices Interspeech 2025