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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)

Retrieved Sequence Augmentation for Protein Representation Learning EMNLP 2024 Retrieve-Plan-Generation: An Iterative Planning and Answering Framework for Knowledge-Intensive LLM Generation EMNLP 2024 Retrieving Contextual Information for Long-Form Question Answering using Weak Supervision EMNLP 2024 Retrieving Examples from Memory for Retrieval Augmented Neural Machine Translation: A Systematic Comparison NAACL 2024 Retrieving Semantics for Fact-Checking: A Comparative Approach using CQ (Claim to Question) & AQ (Answer to Question) EMNLP 2024 RetroOOD: Understanding Out-of-Distribution Generalization in Retrosynthesis Prediction AAAI 2024 Re-Tuning: Overcoming the Compositionality Limits of Large Language Models with Recursive Tuning ACL 2024 Return of Unconditional Generation: A Self-supervised Representation Generation Method NeurIPS 2024 Reuse Your Rewards: Reward Model Transfer for Zero-Shot Cross-Lingual Alignment EMNLP 2024 Reusing Transferable Weight Increments for Low-resource Style Generation EMNLP 2024 REValueD: Regularised Ensemble Value-Decomposition for Factorisable Markov Decision Processes ICLR 2024 Revealing Distribution Discrepancy by Sampling Transfer in Unlabeled Data NeurIPS 2024 Revealing Hierarchical Structure of Leaf Venations in Plant Science via Label-Efficient Segmentation: Dataset and Method IJCAI 2024 Revealing the Proximate Long-Tail Distribution in Compositional Zero-Shot Learning AAAI 2024 Revealing the Two Sides of Data Augmentation: An Asymmetric Distillation-based Win-Win Solution for Open-Set Recognition IJCAI 2024 Reverse-Engineering the Reader EMNLP 2024 Reverse Knowledge Distillation: Training a Large Model Using a Small One for Retinal Image Matching on Limited Data WACV 2024 Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference NeurIPS 2024 Review-Enhanced Hierarchical Contrastive Learning for Recommendation AAAI 2024 Reviewing the Forgotten Classes for Domain Adaptation of Black-Box Predictors AAAI 2024 Revisiting Adversarial Patches for Designing Camera-Agnostic Attacks against Person Detection NeurIPS 2024 Revisiting Adversarial Training at Scale CVPR 2024 Revisiting Adversarial Training Under Long-Tailed Distributions CVPR 2024 Revisiting, Benchmarking and Understanding Unsupervised Graph Domain Adaptation NeurIPS 2024 Revisiting Catastrophic Forgetting in Large Language Model Tuning EMNLP 2024