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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 Do Language Models Learn in Context? The Structured Task Hypothesis. ACL 2024 What do Large Language Models Need for Machine Translation Evaluation? EMNLP 2024 whatdoyoumeme at SemEval-2024 Task 4: Hierarchical-Label-Aware Persuasion Detection using Translated Texts SemEval 2024 What happens in continued pre-training? Analysis of self-supervised speech models with continued pre-training for colloquial Finnish ASR Interspeech 2024 What How and When Should Object Detectors Update in Continually Changing Test Domains? CVPR 2024 What if...?: Thinking Counterfactual Keywords Helps to Mitigate Hallucination in Large Multi-modal Models EMNLP 2024 What is lost in Normalization? Exploring Pitfalls in Multilingual ASR Model Evaluations EMNLP 2024 What is the Best Way for ChatGPT to Translate Poetry? ACL 2024 “What is the value of templates?” Rethinking Document Information Extraction Datasets for LLMs EMNLP 2024 What is “Typological Diversity” in NLP? EMNLP 2024 What Kind of Sourcery is This? Evaluating GPT-4’s Performance on Linking Scientific Fact to Citations EMNLP 2024 What Makes a Good Order of Examples in In-Context Learning ACL 2024 What Makes and Breaks Safety Fine-tuning? A Mechanistic Study NeurIPS 2024 What Makes CLIP More Robust to Long-Tailed Pre-Training Data? A Controlled Study for Transferable Insights NeurIPS 2024 What Makes Good Collaborative Views? Contrastive Mutual Information Maximization for Multi-Agent Perception AAAI 2024 What Makes Partial-Label Learning Algorithms Effective? NeurIPS 2024 What Matters in Graph Class Incremental Learning? An Information Preservation Perspective NeurIPS 2024 What Matters in Memorizing and Recalling Facts? Multifaceted Benchmarks for Knowledge Probing in Language Models EMNLP 2024 What Rotary Position Embedding Can Tell Us: Identifying Query and Key Weights Corresponding to Basic Syntactic or High-level Semantic Information NeurIPS 2024 What's in the Flow? Exploiting Temporal Motion Cues for Unsupervised Generic Event Boundary Detection WACV 2024 What's Outside the Intersection? Fine-Grained Error Analysis for Semantic Segmentation Beyond IoU WACV 2024 What the Weight?! A Unified Framework for Zero-Shot Knowledge Composition EACL 2024 What to Annotate: Retrieving Lexical Markers of Conspiracy Discourse from an Italian-English Corpus of Telegram Data COLING 2024 What to Remember: Self-Adaptive Continual Learning for Audio Deepfake Detection AAAI 2024 What to Say and When to Say it: Live Fitness Coaching as a Testbed for Situated Interaction NeurIPS 2024