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)

Discriminative Appearance Modeling With Multi-Track Pooling for Real-Time Multi-Object Tracking CVPR 2021 Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation AAAI 2021 Disentangled Cycle Consistency for Highly-Realistic Virtual Try-On CVPR 2021 Disentangled Information Bottleneck AAAI 2021 Disentangled Recurrent Wasserstein Autoencoder ICLR 2021 Disentangled Representation Learning in Heterogeneous Information Network for Large-scale Android Malware Detection in the COVID-19 Era and Beyond AAAI 2021 Disentangling 3D Prototypical Networks for Few-Shot Concept Learning ICLR 2021 Disentangling Representations of Text by Masking Transformers EMNLP 2021 Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence Annotation EMNLP 2021 Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing EMNLP 2021 Distilling Audio-Visual Knowledge by Compositional Contrastive Learning CVPR 2021 Distilling Knowledge for Empathy Detection EMNLP 2021 Distilling Knowledge via Knowledge Review CVPR 2021 Distilling Linguistic Context for Language Model Compression EMNLP 2021 Distilling Localization for Self-Supervised Representation Learning AAAI 2021 Distilling Meta Knowledge on Heterogeneous Graph for Illicit Drug Trafficker Detection on Social Media NeurIPS 2021 Distilling Object Detectors via Decoupled Features CVPR 2021 Distilling Relation Embeddings from Pretrained Language Models EMNLP 2021 Distilling Robust and Non-Robust Features in Adversarial Examples by Information Bottleneck NeurIPS 2021 Distilling the Knowledge of Large-scale Generative Models into Retrieval Models for Efficient Open-domain Conversation EMNLP 2021 Distilling Word Meaning in Context from Pre-trained Language Models EMNLP 2021 Distributed Representations of Emotion Categories in Emotion Space ACL 2021 Distribution Alignment: A Unified Framework for Long-Tail Visual Recognition CVPR 2021 Distributionally Robust Optimization for Deep Kernel Multiple Instance Learning AISTATS 2021 Distributional Reinforcement Learning via Moment Matching AAAI 2021