conftrace_

Learning Types

32,670 papers (1 classified directly here)

Subtopics · a paper can sit in several, so these overlap

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)

Papers per year

1

22

25

29

26

38

46

60

109

129

179

310

686

1,294

2,286

3,018

3,254

3,930

4,067

4,819

5,737

2,605

'10

'15

'20

'25

Papers (including subtopics)

Learning to Autofocus CVPR 2020 Learning to Cartoonize Using White-Box Cartoon Representations CVPR 2020 Learning to Classify Intents and Slot Labels Given a Handful of Examples ACL 2020 Learning to Classify the Wrong Answers for Multiple Choice Question Answering (Student Abstract) AAAI 2020 Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules ICML 2020 Learning to Compare for Better Training and Evaluation of Open Domain Natural Language Generation Models AAAI 2020 Learning to Contextually Aggregate Multi-Source Supervision for Sequence Labeling ACL 2020 Learning to Contrast the Counterfactual Samples for Robust Visual Question Answering EMNLP 2020 Learning to Correspond Dynamical Systems L4DC 2020 Learning to Detect Important People in Unlabelled Images for Semi-Supervised Important People Detection CVPR 2020 Learning to Discriminate Information for Online Action Detection CVPR 2020 Learning to Generate 3D Training Data Through Hybrid Gradient CVPR 2020 Learning to Generate Maps from Trajectories AAAI 2020 Learning to Have an Ear for Face Super-Resolution CVPR 2020 Learning to Incorporate Structure Knowledge for Image Inpainting AAAI 2020 Learning to Learn Cropping Models for Different Aspect Ratio Requirements CVPR 2020 Learning to Learn Single Domain Generalization CVPR 2020 Learning to Learn to Disambiguate: Meta-Learning for Few-Shot Word Sense Disambiguation EMNLP 2020 Learning to Map Frequent Phrases to Sub-Structures of Meaning Representation for Neural Semantic Parsing AAAI 2020 Learning to Mutate with Hypergradient Guided Population NeurIPS 2020 Learning to Observe: Approximating Human Perceptual Thresholds for Detection of Suprathreshold Image Transformations CVPR 2020 Learning to Plan and Realize Separately for Open-Ended Dialogue Systems EMNLP 2020 Learning to Reason: Leveraging Neural Networks for Approximate DNF Counting AAAI 2020 Learning to Recover from Multi-Modality Errors for Non-Autoregressive Neural Machine Translation ACL 2020 Learning to Represent Image and Text with Denotation Graph EMNLP 2020