Skip to content
conftrace_

Learning Types

56,253 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Self-Supervised Learning (8,965) Adversarial Learning (5,204) Unsupervised Learning (4,874) Transfer Learning (4,808) Weakly Supervised Learning (3,938) Contrastive Learning (3,748) Zero-Shot Learning (3,130) Semi-Supervised Learning (3,128) Reinforcement Learning (3,118) Multi-Task Learning (2,556) Evaluation (2,164) Continual Learning (2,107) Active Learning (1,983) Few-Shot Learning (1,840) Deep Learning (1,404) Online Learning (1,360) Multi-Armed Bandits (1,327) Multimodal Learning (1,289) Supervised Learning (986) Multi-Agent Systems (813) Uncertainty Quantification (805) Causal Inference (636) Robustness (576) Retrieval-Augmented Generation (565) Fine-Tuning (490) Ensemble Learning (482) In-Context Learning (439) Multi-Label Classification (430) Imitation Learning (387) Prompt Engineering (270) Multi-Lingual Learning (269) Distribution Shift (264) Reinforcement Learning from Human Feedback (209) Regularization (207) Exploration-Exploitation (203) Generative Models (200) Multi-Objective Optimization (185) Out-of-Distribution Detection (176) Sparse Learning (165) Sampling (150) Preference Learning (136) Offline Reinforcement Learning (130) Multi-Label Learning (128) Markov Decision Process (127) Neural Architecture Search (122) Multi-Instance Learning (121) Multi-View Learning (117) Robust Learning (110) Generative Model (110) Time Series (108) Large Language Models (104) Exploration (103) Hyperparameter Optimization (99) Machine Unlearning (95) Imbalanced Learning (93) Machine Translation (93) Multi-Class Classification (85) Differential Privacy (82) Time Series Analysis (71) Reasoning (70) Calibration (67) Structure Learning (66) Physics-Informed Learning (62) Class Imbalance (58) Model-Based RL (55) Interactive Learning (55) Multi-Domain Learning (47) Inverse Reinforcement Learning (46) Crowdsourcing (40) Off-Policy Learning (38) Label Noise (38) Noisy Label Learning (35) Offline RL (32) Attention (32) Evolutionary Algorithm (32) Decision Making (31) Policy Learning (30) Personalization (28) Low-Resource Learning (26) Collaborative Filtering (25) Self-Training (24) Sequential Modeling (24) Parameter Estimation (23) Survival Analysis (21) Machine Learning (20) Parameter-Efficient Fine-Tuning (20) Synthetic Data Generation (20) Annotation (18) Symbolic Regression (18) AutoML (16) Security (15) Multi-Source Learning (13) Distant Supervision (13) Text Generation (11) Distributional Reinforcement Learning (9) Sentiment Analysis (9) Multi-Hop Reasoning (9) Language Modeling (9) Code Generation (8) Multi-Object Tracking (8) Natural Language Inference (7) Chain-of-Thought (6) Question Answering (5)

Papers per year

1
20
220
477
4,652
9,258
2000
'5
'10
'15
'20
'25

Papers (including subtopics)

Fake News Detection Strategies under Dataset Bias: Using Large-scale Coarse-grained Labels EACL 2026 False Alarm Rectification for Early Smoke Segmentation WACV 2026 False Positives Matter: Multidimensional Localization Evaluation and Training-Free Explainable Adversarial Patch Defense AAAI 2026 FAM: Fine-Grained Alignment Matters in Multimodal Embedding Learning with Large Vision-Language Models AAAI 2026 FaNe: Towards Fine-Grained Cross-Modal Contrast with False-Negative Reduction and Text-Conditioned Sparse Attention AAAI 2026 FANoise: Singular Value-Adaptive Noise Modulation for Robust Multimodal Representation Learning AAAI 2026 Farhan Nafis Rayhan at SemEval-2026 Task 13: Supervised Contrastive Learning Approach with Gated Multiclass Decomposition Ensemble Architecture for Code Authorship Identification SemEval 2026 Fast Best-in-Class Regret for Contextual Bandits UAI 2026 FAST-EQA: Efficient Embodied Question Answering with Global and Local Region Relevancy WACV 2026 Fault Diagnosis of Irregular Sequences by Adjoint Learning in Continuous-Time Model Space AAAI 2026 Feature-Centric Unsupervised Node Representation Learning Without Homophily Assumption AAAI 2026 Feature Compression May Be the Root Cause of Adversarial Fragility in Neural Network Classifiers (Student Abstract) AAAI 2026 FedAlign: Differentially Private Distribution Alignment for Non-IID Federated Learning CVPR 2026 FedARA: Resource-adaptive Low-rank Personalized Federated Learning via Anchor-driven Representation Alignment on Heterogeneous Edge Devices CVPR 2026 FedAU2: Attribute Unlearning for User-Level Federated Recommender Systems with Adaptive and Robust Adversarial Training AAAI 2026 FedCART: Tackling Long-Tailed Distributions in Federated Adversarial Training via Classifier Refinement CVPR 2026 Federated Active Learning Under Extreme Non-IID and Global Class Imbalance CVPR 2026 Federated Combinatorial Causal Bandits with Heterogeneous Causal Influences UAI 2026 Federated Context-Aware Personalized Recommendation AAAI 2026 FedHarmony: Harmonizing Heterogeneous Label Correlations in Federated Multi-Label Learning CVPR 2026 FedRG: Unleashing the Representation Geometry for Federated Learning with Noisy Clients CVPR 2026 FedRNC: Addressing Spatio-Temporal Label Misalignment in Federated Noisy Class-Incremental Learning AAAI 2026 Feedback-Aware Prompt Optimization Framework for Generating Job Postings EACL 2026 Feeling Right vs. Being Right: How AI Sycophancy Affects Value-Laden Deliberation ACL 2026 Few-for-Many Personalized Federated Learning CVPR 2026