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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

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20
220
477
4,652
9,258
2000
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Papers (including subtopics)

Inconsistency-Based Data-Centric Active Open-Set Annotation AAAI 2024 In-Context Compositional Generalization for Large Vision-Language Models EMNLP 2024 In-context Contrastive Learning for Event Causality Identification EMNLP 2024 In-Context Example Retrieval from Multi-Perspectives for Few-Shot Aspect-Based Sentiment Analysis COLING 2024 In-context Exploration-Exploitation for Reinforcement Learning ICLR 2024 In-context Learning and Gradient Descent Revisited NAACL 2024 In-Context Learning May Not Elicit Trustworthy Reasoning: A-Not-B Errors in Pretrained Language Models EMNLP 2024 In-Context Learning of a Linear Transformer Block: Benefits of the MLP Component and One-Step GD Initialization NeurIPS 2024 In-Context Learning State Vector with Inner and Momentum Optimization NeurIPS 2024 In-Context Learning with Iterative Demonstration Selection EMNLP 2024 In-Context Learning with Representations: Contextual Generalization of Trained Transformers NeurIPS 2024 In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness NeurIPS 2024 In-Context Matting CVPR 2024 In-context Mixing (ICM): Code-mixed Prompts for Multilingual LLMs ACL 2024 In-Context Pretraining: Language Modeling Beyond Document Boundaries ICLR 2024 In-Context Symbolic Regression: Leveraging Large Language Models for Function Discovery ACL 2024 In-Context Symmetries: Self-Supervised Learning through Contextual World Models NeurIPS 2024 Incorporating Dialect Understanding Into LLM Using RAG and Prompt Engineering Techniques for Causal Commonsense Reasoning NAACL 2024 Incorporating Geo-Diverse Knowledge into Prompting for Increased Geographical Robustness in Object Recognition CVPR 2024 Incorporating Lexical and Syntactic Knowledge for Unsupervised Cross-Lingual Transfer COLING 2024 Incorporating Schema-Aware Description into Document-Level Event Extraction IJCAI 2024 Incorporating Syntax and Lexical Knowledge to Multilingual Sentiment Classification on Large Language Models ACL 2024 Incorporating Word Count Information into Depression Risk Summary Generation: INF@UoS CLPsych 2024 Submission EACL 2024 Increasing the Difficulty of Automatically Generated Questions via Reinforcement Learning with Synthetic Preference for Cost-Effective Cultural Heritage Dataset Generation EMNLP 2024 Incremental Learning of Retrievable Skills For Efficient Continual Task Adaptation NeurIPS 2024