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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)

Exploring Hint Generation Approaches for Open-Domain Question Answering EMNLP 2024 Exploring Intrinsic Language-specific Subspaces in Fine-tuning Multilingual Neural Machine Translation EMNLP 2024 Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations AAAI 2024 Exploring Learngene via Stage-wise Weight Sharing for Initializing Variable-sized Models IJCAI 2024 Exploring Mathematical Extrapolation of Large Language Models with Synthetic Data ACL 2024 Exploring Memorization in Fine-tuned Language Models ACL 2024 Exploring Molecular Pretraining Model at Scale NeurIPS 2024 Exploring Ordinality in Text Classification: A Comparative Study of Explicit and Implicit Techniques ACL 2024 Exploring Pose-Aware Human-Object Interaction via Hybrid Learning CVPR 2024 Exploring Question Guidance and Answer Calibration for Visually Grounded Video Question Answering EMNLP 2024 Exploring Structured Semantic Priors Underlying Diffusion Score for Test-time Adaptation NeurIPS 2024 Exploring the Capability of Multimodal LLMs with Yonkoma Manga: The YManga Dataset and Its Challenging Tasks EMNLP 2024 Exploring the Compositional Deficiency of Large Language Models in Mathematical Reasoning Through Trap Problems EMNLP 2024 Exploring the Edges of Latent State Clusters for Goal-Conditioned Reinforcement Learning NeurIPS 2024 Exploring the limits of decoder-only models trained on public speech recognition corpora Interspeech 2024 Exploring the Practicality of Generative Retrieval on Dynamic Corpora EMNLP 2024 Exploring the Relationship between In-Context Learning and Instruction Tuning EMNLP 2024 Exploring the Role of Reasoning Structures for Constructing Proofs in Multi-Step Natural Language Reasoning with Large Language Models EMNLP 2024 Exploring Vision Transformers for 3D Human Motion-Language Models with Motion Patches CVPR 2024 Exponential Quantum Communication Advantage in Distributed Inference and Learning NeurIPS 2024 Exposing the Deception: Uncovering More Forgery Clues for Deepfake Detection AAAI 2024 Expressive Losses for Verified Robustness via Convex Combinations ICLR 2024 Expressive Multi-Agent Communication via Identity-Aware Learning AAAI 2024 Extending AZee with Non-manual Gesture Rules for French Sign Language COLING 2024 Extending Multi-modal Contrastive Representations NeurIPS 2024