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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)

What Variables Affect Out-of-Distribution Generalization in Pretrained Models? NeurIPS 2024 What When and Where? Self-Supervised Spatio-Temporal Grounding in Untrimmed Multi-Action Videos from Narrated Instructions CVPR 2024 When 3D Bounding-Box Meets SAM: Point Cloud Instance Segmentation With Weak-and-Noisy Supervision WACV 2024 When ”A Helpful Assistant” Is Not Really Helpful: Personas in System Prompts Do Not Improve Performances of Large Language Models EMNLP 2024 When are dynamical systems learned from time series data statistically accurate? NeurIPS 2024 When Are Two Lists Better than One?: Benefits and Harms in Joint Decision-Making AAAI 2024 When Argumentation Meets Cohesion: Enhancing Automatic Feedback in Student Writing COLING 2024 When Causal Inference Meets Graph Machine Learning AAAI 2024 When Does Monolingual Data Help Multilingual Translation: The Role of Domain and Model Scale NAACL 2024 When does perceptual alignment benefit vision representations? NeurIPS 2024 When do Generative Query and Document Expansions Fail? A Comprehensive Study Across Methods, Retrievers, and Datasets EACL 2024 When Do LLMs Need Retrieval Augmentation? Mitigating LLMs’ Overconfidence Helps Retrieval Augmentation ACL 2024 When Generative Adversarial Networks Meet Sequence Labeling Challenges EMNLP 2024 When is a Metaphor Actually Novel? Annotating Metaphor Novelty in the Context of Automatic Metaphor Detection EACL 2024 When Is a Name Sensitive? Eponyms in Clinical Text and Implications for De-Identification EACL 2024 When Is Inductive Inference Possible? NeurIPS 2024 When is Multicalibration Post-Processing Necessary? NeurIPS 2024 When Is Multilinguality a Curse? Language Modeling for 250 High- and Low-Resource Languages EMNLP 2024 When Life Gives You Lemons, Make Cherryade: Converting Feedback from Bad Responses into Good Labels NAACL 2024 When LLM Meets DRL: Advancing Jailbreaking Efficiency via DRL-guided Search NeurIPS 2024 When LLMs Meets Acoustic Landmarks: An Efficient Approach to Integrate Speech into Large Language Models for Depression Detection EMNLP 2024 When Model Meets New Normals: Test-Time Adaptation for Unsupervised Time-Series Anomaly Detection AAAI 2024 When No-Rejection Learning is Consistent for Regression with Rejection AISTATS 2024 When Parts Are Greater Than Sums: Individual LLM Components Can Outperform Full Models EMNLP 2024 When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications? EMNLP 2024