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Learning Types

56,253 papers (3 classified directly here)

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)
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Papers (including subtopics)

Arbitrariness and Social Prediction: The Confounding Role of Variance in Fair Classification AAAI 2024 ARC: A Generalist Graph Anomaly Detector with In-Context Learning NeurIPS 2024 ArcAid: Analysis of Archaeological Artifacts Using Drawings WACV 2024 ArchLock: Locking DNN Transferability at the Architecture Level with a Zero-Cost Binary Predictor ICLR 2024 Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantification NeurIPS 2024 Are AI-Generated Text Detectors Robust to Adversarial Perturbations? ACL 2024 A Recipe for Improved Certifiable Robustness ICLR 2024 A Recipe for Scaling up Text-to-Video Generation with Text-free Videos CVPR 2024 Are Data Augmentation Methods in Named Entity Recognition Applicable for Uncertainty Estimation? EMNLP 2024 Are Emergent Abilities in Large Language Models just In-Context Learning? ACL 2024 Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks? NeurIPS 2024 Are Human-generated Demonstrations Necessary for In-context Learning? ICLR 2024 A Reinforcement-Learning-Based Multiple-Column Selection Strategy for Column Generation AAAI 2024 Are Language Models Actually Useful for Time Series Forecasting? NeurIPS 2024 Are Large Language Models Consistent over Value-laden Questions? EMNLP 2024 Are Large Language Models Good Statisticians? NeurIPS 2024 Are Large Language Models (LLMs) Good Social Predictors? EMNLP 2024 Are Large Language Models State-of-the-art Quality Estimators for Machine Translation of User-generated Content? EMNLP 2024 Are LLMs Capable of Data-based Statistical and Causal Reasoning? Benchmarking Advanced Quantitative Reasoning with Data ACL 2024 Are LLMs Good Zero-Shot Fallacy Classifiers? EMNLP 2024 Are Machines Better at Complex Reasoning? Unveiling Human-Machine Inference Gaps in Entailment Verification ACL 2024 Are modern neural ASR architectures robust for polysynthetic languages? EMNLP 2024 Are More LLM Calls All You Need? Towards the Scaling Properties of Compound AI Systems NeurIPS 2024 Are Natural Domain Foundation Models Useful for Medical Image Classification? WACV 2024 Are Recent Deep Learning-Based Speech Enhancement Methods Ready to Confront Real-World Noisy Environments? Interspeech 2024