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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)

The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning ICLR 2024 The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better NeurIPS 2024 The Unreasonable Effectiveness of Easy Training Data for Hard Tasks ACL 2024 The Unreasonable Effectiveness of Pre-Trained Features for Camera Pose Refinement CVPR 2024 The Value of Reward Lookahead in Reinforcement Learning NeurIPS 2024 The Vedic Compound Dataset COLING 2024 Think Before You Duel: Understanding Complexities of Preference Learning under Constrained Resources AISTATS 2024 Think Global, Adapt Local: Learning Locally Adaptive K-Nearest Neighbor Kernel Density Estimators AISTATS 2024 “Thinking” Fair and Slow: On the Efficacy of Structured Prompts for Debiasing Language Models EMNLP 2024 Thinking Outside of the Differential Privacy Box: A Case Study in Text Privatization with Language Model Prompting EMNLP 2024 Think Twice Before Selection: Federated Evidential Active Learning for Medical Image Analysis with Domain Shifts CVPR 2024 Think Twice: Perspective-Taking Improves Large Language Models’ Theory-of-Mind Capabilities ACL 2024 Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox NeurIPS 2024 Thompson Sampling for Real-Valued Combinatorial Pure Exploration of Multi-Armed Bandit AAAI 2024 Thompson Sampling Itself is Differentially Private AISTATS 2024 Threaten Spiking Neural Networks through Combining Rate and Temporal Information ICLR 2024 Three Heads Are Better than One: Complementary Experts for Long-Tailed Semi-supervised Learning AAAI 2024 Three Heads Are Better than One: Improving Cross-Domain NER with Progressive Decomposed Network AAAI 2024 TI2V-Zero: Zero-Shot Image Conditioning for Text-to-Video Diffusion Models CVPR 2024 TiC-CLIP: Continual Training of CLIP Models ICLR 2024 Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective NeurIPS 2024 Tight Rates for Bandit Control Beyond Quadratics NeurIPS 2024 TIKP: Text-to-Image Knowledge Preservation for Continual Semantic Segmentation AAAI 2024 Time-Aware Knowledge Representations of Dynamic Objects with Multidimensional Persistence AAAI 2024 TimeBench: A Comprehensive Evaluation of Temporal Reasoning Abilities in Large Language Models ACL 2024