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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)

TopoSlide: Topologically-Informed Histopathology Whole Slide Image Representation Learning CVPR 2026 To Think or Not to Think: The Hidden Cost of Meta-Training with Excessive CoT Examples ACL 2026 Toward Diffusible High-Dimensional Latent Spaces: A Frequency Perspective CVPR 2026 Toward Real-world Infrared Image Super-Resolution: A Unified Autoregressive Framework and Benchmark Dataset CVPR 2026 Toward Robust In-Context Learning: Leveraging Out-of-distribution Proxies for Target Inaccessible Demonstration Retrieval ACL 2026 Towards an Incremental Unified Multimodal Anomaly Detection: Augmenting Multimodal Denoising From an Information Bottleneck Perspective CVPR 2026 Towards Balanced Multi-Modal Learning in 3D Human Pose Estimation CVPR 2026 Towards Calibrating Prompt Tuning of Vision- Language Models CVPR 2026 Towards Decompositional Human Motion Generation with Energy-Based Diffusion Models CVPR 2026 Towards Dynamic Modality Alignment in Multimodal Continual Learning CVPR 2026 Toward Secure Tuning: Mitigating Security Risks from Instruction Fine-Tuning ACL 2026 Towards Effective Surgical Representation Learning with DINO Models MIDL 2026 Towards Efficient Medical Reasoning with Minimal Fine-Tuning Data CVPR 2026 Towards Faithful Industrial RAG: A Reinforced Co-adaptation Framework for Advertising QA ACL 2026 Towards Fine-Grained and Multi-Granular Contrastive Language-Speech Pre-training ACL 2026 Towards Fine-Grained Attribution: Instance-Aware Preference Optimization for Aligning Diffusion Models CVPR 2026 Towards Foundation Models for 3D Scene Understanding: Instance-Aware Self-Supervised Learning for Point Clouds CVPR 2026 Towards Generalizable AI-Generated Image Detection via Image-Adaptive Prompt Learning CVPR 2026 Towards Generalized Multimodal Homography Estimation CVPR 2026 Towards Generalized Representations for Low-Light Understanding: When Signal Constancy Meets Semantic Enrichment CVPR 2026 Towards High-Fidelity, Identity-Preserving Real-Time Makeup Transfer: Decoupling Style Generation WACV 2026 Towards High-resolution and Disentangled Reference-based Sketch Colorization CVPR 2026 Towards Modality-Agnostic Continual Domain-Incremental Brain Lesion Segmentation MIDL 2026 Towards Multimodal Domain Generalization with Few Labels CVPR 2026 Towards Privacy-Preserving Large Language Model: Text-free Inference Through Alignment and Adaptation ACL 2026