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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)

Horizon-Free and Instance-Dependent Regret Bounds for Reinforcement Learning with General Function Approximation AISTATS 2024 Horizon-Free Regret for Linear Markov Decision Processes ICLR 2024 Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs ICLR 2024 How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition ACL 2024 How Are Metaphors Processed by Language Models? The Case of Analogies CoNLL 2024 How Can Client Motivational Language Inform Psychotherapy Agents? EACL 2024 How Do Conversational Agents in Healthcare Impact on Patient Agency? EACL 2024 How does Architecture Influence the Base Capabilities of Pre-trained Language Models? A Case Study Based on FFN-Wider and MoE Transformers NeurIPS 2024 How Does Beam Search improve Span-Level Confidence Estimation in Generative Sequence Labeling? EACL 2024 How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach NeurIPS 2024 How does Multi-Task Training Affect Transformer In-Context Capabilities? Investigations with Function Classes NAACL 2024 How Does the Disclosure of AI Assistance Affect the Perceptions of Writing? EMNLP 2024 How Does the Textual Information Affect the Retrieval of Multimodal In-Context Learning? EMNLP 2024 How Does Unlabeled Data Provably Help Out-of-Distribution Detection? ICLR 2024 How Does Variance Shape the Regret in Contextual Bandits? NeurIPS 2024 How Do Humans Write Code? Large Models Do It the Same Way Too EMNLP 2024 How Do Large Language Models Acquire Factual Knowledge During Pretraining? NeurIPS 2024 How do Large Language Models Learn In-Context? Query and Key Matrices of In-Context Heads are Two Towers for Metric Learning EMNLP 2024 How Far Can In-Context Alignment Go? Exploring the State of In-Context Alignment EMNLP 2024 How Far Can Transformers Reason? The Globality Barrier and Inductive Scratchpad NeurIPS 2024 How Far Can We Extract Diverse Perspectives from Large Language Models? EMNLP 2024 How Good is a Single Basin? AISTATS 2024 How Hard is this Test Set? NLI Characterization by Exploiting Training Dynamics EMNLP 2024 How Important is a Language Model for Low-resource ASR? ACL 2024 How JEPA Avoids Noisy Features: The Implicit Bias of Deep Linear Self Distillation Networks NeurIPS 2024