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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)

Rethinking Deep Image Prior for Denoising ICCV 2021 Rethinking Graph Regularization for Graph Neural Networks AAAI 2021 Rethinking Label-Wise Cross-Modal Retrieval from A Semantic Sharing Perspective IJCAI 2021 Rethinking Neural Operations for Diverse Tasks NeurIPS 2021 Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss ICML 2021 Rethinking Text Segmentation: A Novel Dataset and a Text-Specific Refinement Approach CVPR 2021 Rethinking the Backdoor Attacks' Triggers: A Frequency Perspective ICCV 2021 Rethinking the Heatmap Regression for Bottom-Up Human Pose Estimation CVPR 2021 Rethinking Why Intermediate-Task Fine-Tuning Works EMNLP 2021 Rethinking Zero-shot Neural Machine Translation: From a Perspective of Latent Variables EMNLP 2021 [RETRACTED] Breaking the Corpus Bottleneck for Context-Aware Neural Machine Translation with Cross-Task Pre-training ACL 2021 [RETRACTED] DMix: Distance Constrained Interpolative Mixup EMNLP 2021 RETRACTED: Multi-modal Graph Fusion for Named Entity Recognition with Targeted Visual Guidance AAAI 2021 [RETRACTED] Sequence Mixup for Zero-Shot Cross-Lingual Part-Of-Speech Tagging EMNLP 2021 Retrieval, Analogy, and Composition: A framework for Compositional Generalization in Image Captioning EMNLP 2021 Retrieval Augmentation Reduces Hallucination in Conversation EMNLP 2021 Retrieval Augmented Code Generation and Summarization EMNLP 2021 Retrospective Reader for Machine Reading Comprehension AAAI 2021 Return-Based Contrastive Representation Learning for Reinforcement Learning ICLR 2021 Revisiting Few-sample BERT Fine-tuning ICLR 2021 Revisiting Iterative Back-Translation from the Perspective of Compositional Generalization AAAI 2021 Revisiting Knowledge Distillation: An Inheritance and Exploration Framework CVPR 2021 Revisiting Rainbow: Promoting more insightful and inclusive deep reinforcement learning research ICML 2021 Revisiting ResNets: Improved Training and Scaling Strategies NeurIPS 2021 Revisiting the Negative Data of Distantly Supervised Relation Extraction ACL 2021