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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)

Improved Self-Training for Test-Time Adaptation CVPR 2024 Improved Visual Grounding through Self-Consistent Explanations CVPR 2024 Improved Zero-Shot Classification by Adapting VLMs with Text Descriptions CVPR 2024 Improve Meta-learning for Few-Shot Text Classification with All You Can Acquire from the Tasks EMNLP 2024 Improve Robustness of Reinforcement Learning against Observation Perturbations via l∞ Lipschitz Policy Networks AAAI 2024 Improving Acoustic Word Embeddings through Correspondence Training of Self-supervised Speech Representations EACL 2024 Improving Adversarial Data Collection by Supporting Annotators: Lessons from GAHD, a German Hate Speech Dataset NAACL 2024 Improving Adversarial Robustness in Vision-Language Models with Architecture and Prompt Design EMNLP 2024 Improving Adversarial Robustness via Feature Pattern Consistency Constraint IJCAI 2024 Improving Argument Effectiveness Across Ideologies using Instruction-tuned Large Language Models EMNLP 2024 Improving Attributed Text Generation of Large Language Models via Preference Learning ACL 2024 Improving Audio Classification with Low-Sampled Microphone Input: An Empirical Study Using Model Self-Distillation Interspeech 2024 Improving Content Recommendation: Knowledge Graph-Based Semantic Contrastive Learning for Diversity and Cold-Start Users COLING 2024 Improving Context-Aware Preference Modeling for Language Models NeurIPS 2024 Improving Continual Few-shot Relation Extraction through Relational Knowledge Distillation and Prototype Augmentation COLING 2024 Improving Contrastive Learning in Emotion Recognition in Conversation via Data Augmentation and Decoupled Neutral Emotion EACL 2024 Improving Covert Toxicity Detection by Retrieving and Generating References NAACL 2024 Improving Cross-lingual Transfer with Contrastive Negative Learning and Self-training COLING 2024 Improving Decision Sparsity NeurIPS 2024 Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn NeurIPS 2024 Improving Demonstration Diversity by Human-Free Fusing for Text-to-SQL EMNLP 2024 Improving Dialog Safety using Socially Aware Contrastive Learning EACL 2024 Improving Discriminative Capability of Reward Models in RLHF Using Contrastive Learning EMNLP 2024 Improving Event Definition Following For Zero-Shot Event Detection ACL 2024 Improving Factual Consistency of News Summarization by Contrastive Preference Optimization EMNLP 2024