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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)

Barely Supervised Learning for Graph-Based Fraud Detection AAAI 2024 “Barking up the Right Tree”, a GAN-Based Pun Generation Model through Semantic Pruning COLING 2024 Basque and Spanish Counter Narrative Generation: Data Creation and Evaluation COLING 2024 Batch-ICL: Effective, Efficient, and Order-Agnostic In-Context Learning ACL 2024 BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference ICLR 2024 Bayesian Calibration of Win Rate Estimation with LLM Evaluators EMNLP 2024 Bayesian Domain Adaptation with Gaussian Mixture Domain-Indexing NeurIPS 2024 Bayesian Example Selection Improves In-Context Learning for Speech, Text and Visual Modalities EMNLP 2024 Bayesian Exploration of Pre-trained Models for Low-shot Image Classification CVPR 2024 Bayesian Nonparametrics Meets Data-Driven Distributionally Robust Optimization NeurIPS 2024 Bayesian Online Learning for Consensus Prediction AISTATS 2024 Bayesian Prompt Ensembles: Model Uncertainty Estimation for Black-Box Large Language Models ACL 2024 Bayesian Semi-structured Subspace Inference AISTATS 2024 BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction ICLR 2024 BBRC: Brazilian Banking Regulation Corpora COLING 2024 Beam Enumeration: Probabilistic Explainability For Sample Efficient Self-conditioned Molecular Design ICLR 2024 Be a Multitude to Itself: A Prompt Evolution Framework for Red Teaming EMNLP 2024 BeanCounter: A low-toxicity, large-scale, and open dataset of business-oriented text NeurIPS 2024 Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference ICLR 2024 BECLR: Batch Enhanced Contrastive Few-Shot Learning ICLR 2024 Be Confident in What You Know: Bayesian Parameter Efficient Fine-Tuning of Vision Foundation Models NeurIPS 2024 BEEAR: Embedding-based Adversarial Removal of Safety Backdoors in Instruction-tuned Language Models EMNLP 2024 BeliefFlow: A Framework for Logic-Based Belief Diffusion via Iterated Belief Change AAAI 2024 Belief Revision: The Adaptability of Large Language Models Reasoning EMNLP 2024 Belief-State Query Policies for User-Aligned POMDPs NeurIPS 2024