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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)

Architectural Sweet Spots for Modeling Human Label Variation by the Example of Argument Quality: It’s Best to Relate Perspectives! EMNLP 2023 Architecture-Agnostic Masked Image Modeling -- From ViT back to CNN ICML 2023 Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning NeurIPS 2023 ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations ICLR 2023 A Read-and-Select Framework for Zero-shot Entity Linking EMNLP 2023 Are aligned neural networks adversarially aligned? NeurIPS 2023 Are Binary Annotations Sufficient? Video Moment Retrieval via Hierarchical Uncertainty-Based Active Learning CVPR 2023 Are Data-Driven Explanations Robust Against Out-of-Distribution Data? CVPR 2023 A Reduction-based Framework for Sequential Decision Making with Delayed Feedback NeurIPS 2023 Are labels informative in semi-supervised learning? Estimating and leveraging the missing-data mechanism. ICML 2023 Are Language Models Worse than Humans at Following Prompts? It’s Complicated EMNLP 2023 Are Large Language Models Reliable Judges? A Study on the Factuality Evaluation Capabilities of LLMs EMNLP 2023 A Relaxed Inertial Forward-Backward-Forward Algorithm for Solving Monotone Inclusions with Application to GANs JMLR 2023 Are Layout-Infused Language Models Robust to Layout Distribution Shifts? A Case Study with Scientific Documents ACL 2023 Are Machine Rationales (Not) Useful to Humans? Measuring and Improving Human Utility of Free-text Rationales ACL 2023 Are NLP Models Good at Tracing Thoughts: An Overview of Narrative Understanding EMNLP 2023 Are Personalized Stochastic Parrots More Dangerous? Evaluating Persona Biases in Dialogue Systems EMNLP 2023 Are Sample-Efficient NLP Models More Robust? ACL 2023 Are Structural Concepts Universal in Transformer Language Models? Towards Interpretable Cross-Lingual Generalization EMNLP 2023 Are Synonym Substitution Attacks Really Synonym Substitution Attacks? ACL 2023 Are the Best Multilingual Document Embeddings simply Based on Sentence Embeddings? EACL 2023 Are These the Same Apple? Comparing Images Based on Object Intrinsics NeurIPS 2023 Are Transformers Effective for Time Series Forecasting? AAAI 2023 Are Vision Transformers More Data Hungry Than Newborn Visual Systems? NeurIPS 2023 A Rewriting Approach for Gender Inclusivity in Portuguese EMNLP 2023