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Learning Types

32,670 papers (1 classified directly here)

Representation Learning (5,307) Multimodal Learning (3,969) Self-Supervised Learning (3,492) Transfer Learning (2,890) Adversarial Learning (2,199) Deep Learning (1,883) Contrastive Learning (1,730) Reinforcement Learning (1,500) Knowledge Distillation (1,494) Fine-Tuning (1,117) Multi-Task Learning (1,069) Domain Adaptation (977) Zero-Shot Learning (758) Unsupervised Learning (734) Few-Shot Learning (694) Classification (621) Retrieval-Augmented Generation (606) Data Augmentation (583) Semi-Supervised Learning (450) Weakly Supervised Learning (429) Continual Learning (408) In-Context Learning (387) Sequence Modeling (375) Meta-Learning (252) Metric Learning (232) Ensemble Learning (223) Federated Learning (215) Multi-Lingual Learning (199) Robustness (197) Parameter-Efficient Fine-Tuning (190) Imitation Learning (180) Prompt Engineering (170) Chain-of-Thought Reasoning (153) Curriculum Learning (146) Synthetic Data Generation (143) Reinforcement Learning from Human Feedback (141) Multi-Label Classification (123) Regression (117) Generative Model (109) Semantic Segmentation (106) Domain Generalization (105) Uncertainty Quantification (98) Controllable Generation (93) Text Generation (86) Neural Architecture Search (80) Object Detection (80) Image Generation (79) Multi-Agent Systems (76) Feature Learning (74) Preference Learning (73) Machine Translation (71) Out-of-Distribution Detection (68) Machine Unlearning (63) Generation (61) Reasoning (54) Multi-View Learning (53) Time Series (52) Instruction Tuning (50) Distributed Learning (50) Image Restoration (49) Chain-of-Thought (48) Active Learning (47) Text Classification (43) Distribution Shift (43) Structured Prediction (42) Clustering (41) Image Classification (40) Model Merging (37) Sparse Learning (36) Sequence Labeling (36) Multi-Instance Learning (35) Anomaly Detection (33) Image Processing (33) Code Generation (31) Fairness (30) Robust Learning (28) Multi-Domain Learning (27) Supervised Learning (26) Model-Based RL (25) Natural Language Generation (24) Privacy (21) Multi-Objective Optimization (19) Multi-Scale Learning (19) Neural Machine Translation (18) Causal Inference (14) Instance Segmentation (9) Interactive Learning (9) Multi-Label Learning (9) Multi-Source Learning (9) Multi-Class Classification (8)
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Papers (including subtopics)

Can Machines Resonate with Humans? Evaluating the Emotional and Empathic Comprehension of LMs EMNLP 2024 Can Machine Unlearning Reduce Social Bias in Language Models? EMNLP 2024 Can Protective Perturbation Safeguard Personal Data from Being Exploited by Stable Diffusion? CVPR 2024 Can Simple Averaging Defeat Modern Watermarks? NeurIPS 2024 Can Textual Unlearning Solve Cross-Modality Safety Alignment? EMNLP 2024 Can Transformers Smell Like Humans? NeurIPS 2024 CantTalkAboutThis: Aligning Language Models to Stay on Topic in Dialogues EMNLP 2024 Can We Achieve High-quality Direct Speech-to-Speech Translation without Parallel Speech Data? ACL 2024 Can we teach language models to gloss endangered languages? EMNLP 2024 CapHuman: Capture Your Moments in Parallel Universes CVPR 2024 CapsFusion: Rethinking Image-Text Data at Scale CVPR 2024 Capturing Minds, Not Just Words: Enhancing Role-Playing Language Models with Personality-Indicative Data EMNLP 2024 CARAT: Contrastive Feature Reconstruction and Aggregation for Multi-Modal Multi-Label Emotion Recognition AAAI 2024 Carbon Footprint Reduction for Sustainable Data Centers in Real-Time AAAI 2024 CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting ICLR 2024 CARER - ClinicAl Reasoning-Enhanced Representation for Temporal Health Risk Prediction EMNLP 2024 CariesXrays: Enhancing Caries Detection in Hospital-Scale Panoramic Dental X-rays via Feature Pyramid Contrastive Learning AAAI 2024 CASE: Exploiting Intra-class Compactness and Inter-class Separability of Feature Embeddings for Out-of-Distribution Detection AAAI 2024 CA-SSLR: Condition-Aware Self-Supervised Learning Representation for Generalized Speech Processing NeurIPS 2024 Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning ICML 2024 Catastrophic Goodhart: regularizing RLHF with KL divergence does not mitigate heavy-tailed reward misspecification NeurIPS 2024 Catch-Up Mix: Catch-Up Class for Struggling Filters in CNN AAAI 2024 CAT: Exploiting Inter-Class Dynamics for Domain Adaptive Object Detection CVPR 2024 CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentation CVPR 2024 CATS: Enhancing Multivariate Time Series Forecasting by Constructing Auxiliary Time Series as Exogenous Variables ICML 2024