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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)

Test-Time Scaling in Clinical Decision Making MIDL 2026 Test-time Sparsity for Extreme Fast Action Diffusion CVPR 2026 Test-Time Training for LiDAR Semantic Segmentation under Corruption via Geometric Inlier Discrimination CVPR 2026 TexOCR: Advancing Document OCR Models for Compilable Page-to-LaTeX Reconstruction ACL 2026 TextFM: Robust Semi-dense Feature Matching with Language Guidance CVPR 2026 Text-Guided Multi-Scale Frequency Representation Adaptation ACL 2026 TextOVSR: Text-Guided Real-World Opera Video Super-Resolution CVPR 2026 TextPecker: Rewarding Structural Anomaly Quantification for Enhancing Visual Text Rendering CVPR 2026 Text-Printed Image: Bridging the Image-Text Modality Gap for Text-centric Training of Large Vision-Language Models CVPR 2026 Text Slider: Efficient and Plug-and-Play Continuous Concept Control for Image/Video Synthesis via LoRA Adapters WACV 2026 Text-to-Distribution Prediction with Quantile Tokens and Neighbor Context ACL 2026 Texvent: Asynchronous Event Data Simulation via Text Prompt CVPR 2026 TFB at SemEval-2026 Task 4: Diagnosing Model Failures in Narrative Understanding SemEval 2026 TF-CADE: Foreground-Concentrated Text-Video Alignment for Zero-Shot Temporal Action Detection CVPR 2026 TGTrack: Temporal Generative Learning for Unified Single Object Tracking CVPR 2026 TGT: Text-Grounded Trajectories for Locally Controlled Video Generation CVPR 2026 The Argonauts at SemEval 2026 Task 6: Large Language Models for Response Clarity Classification: Prompting, Fine-Tuning, and Data-Centric Approaches SemEval 2026 The Bidirectional Process Reward Model ACL 2026 The Blind Spot of Adaptation: Quantifying and Mitigating Forgetting in Fine-tuned Driving Models CVPR 2026 The Classics at SemEval-2026 Task 3: Combining Transformer Models and LLM-Generated Annotations for Dimensional Aspect-Based Sentiment Analysis SemEval 2026 The Consistency Critic: Correcting Inconsistencies in Generated Images via Reference-Guided Attentive Alignment CVPR 2026 The Counterfactuals at SemEval-2026 Task 9: Can Counterfactually-Inspired Preprocessing help Detect Polarization? SemEval 2026 The Data Frontier for Large Language Models: Selection, Synthesis, and Tools ACL 2026 The Devil Is in Gradient Entanglement: Energy-Aware Gradient Coordinator for Robust Generalized Category Discovery CVPR 2026 The Golden Subspace: Where Efficiency Meets Generalization in Continual Test-Time Adaptation CVPR 2026