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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)

Robust Point Cloud Registration Framework Based on Deep Graph Matching CVPR 2021 Robust Reflection Removal With Reflection-Free Flash-Only Cues CVPR 2021 Robust Regularization with Adversarial Labelling of Perturbed Samples IJCAI 2021 Robust Representation Learning via Perceptual Similarity Metrics ICML 2021 Robust Representation Learning With Feedback for Single Image Deraining CVPR 2021 Robust Retrieval Augmented Generation for Zero-shot Slot Filling EMNLP 2021 RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking EMNLP 2021 RockNER: A Simple Method to Create Adversarial Examples for Evaluating the Robustness of Named Entity Recognition Models EMNLP 2021 RODE: Learning Roles to Decompose Multi-Agent Tasks ICLR 2021 Role of Language Relatedness in Multilingual Fine-tuning of Language Models: A Case Study in Indo-Aryan Languages EMNLP 2021 Role of Optimizer on Network Fine-tuning for Adversarial Robustness (Student Abstract) AAAI 2021 Rotation Equivariant Siamese Networks for Tracking CVPR 2021 Rotation-Invariant Gait Identification with Quaternion Convolutional Neural Networks (Student Abstract) AAAI 2021 RPN Prototype Alignment for Domain Adaptive Object Detector CVPR 2021 RSG: A Simple but Effective Module for Learning Imbalanced Datasets CVPR 2021 RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning AAAI 2021 RTS3D: Real-time Stereo 3D Detection from 4D Feature-Consistency Embedding Space for Autonomous Driving AAAI 2021 Ruddit: Norms of Offensiveness for English Reddit Comments ACL 2021 Rule-based Morphological Inflection Improves Neural Terminology Translation EMNLP 2021 Rumor Detection on Twitter with Claim-Guided Hierarchical Graph Attention Networks EMNLP 2021 S2R-DepthNet: Learning a Generalizable Depth-Specific Structural Representation CVPR 2021 S2VC: A Framework for Any-to-Any Voice Conversion with Self-Supervised Pretrained Representations Interspeech 2021 S3: Learnable Sparse Signal Superdensity for Guided Depth Estimation CVPR 2021 S3: Neural Shape, Skeleton, and Skinning Fields for 3D Human Modeling CVPR 2021 Safe Local Motion Planning With Self-Supervised Freespace Forecasting CVPR 2021