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

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'25

Papers (including subtopics)

UMC: A Unified Bandwidth-efficient and Multi-resolution based Collaborative Perception Framework ICCV 2023 UMD: Unsupervised Model Detection for X2X Backdoor Attacks ICML 2023 UMSE: Unified Multi-scenario Summarization Evaluation ACL 2023 Uncertainty-Aware Alignment Network for Cross-Domain Video-Text Retrieval NeurIPS 2023 Uncertainty-Aware Self-Training for Low-Resource Neural Sequence Labeling AAAI 2023 Uncertainty-Aware Unlikelihood Learning Improves Generative Aspect Sentiment Quad Prediction ACL 2023 Uncertainty-Aware Unsupervised Image Deblurring With Deep Residual Prior CVPR 2023 Uncertainty Estimation for Connectionist Temporal Classification Based Automatic Speech Recognition Interspeech 2023 Uncertainty Estimation for Safety-critical Scene Segmentation via Fine-grained Reward Maximization NeurIPS 2023 Uncertainty Guided Global Memory Improves Multi-Hop Question Answering EMNLP 2023 Uncovering Hidden Consequences of Pre-training Objectives in Sequence-to-Sequence Models ACL 2023 Uncovering Limitations in Text-to-Image Generation: A Contrastive Approach with Structured Semantic Alignment EMNLP 2023 Uncovering the Potential for a Weakly Supervised End-to-End Model in Recognising Speech from Patient with Post-Stroke Aphasia ACL 2023 Uncurated Image-Text Datasets: Shedding Light on Demographic Bias CVPR 2023 Understanding and Bridging the Modality Gap for Speech Translation ACL 2023 Understanding and Improving Features Learned in Deep Functional Maps CVPR 2023 Understanding Contrastive Learning via Distributionally Robust Optimization NeurIPS 2023 Understanding In-Context Learning via Supportive Pretraining Data ACL 2023 Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data AISTATS 2023 Understanding Neural Network Binarization with Forward and Backward Proximal Quantizers NeurIPS 2023 Understanding Plasticity in Neural Networks ICML 2023 Understanding Programs by Exploiting (Fuzzing) Test Cases ACL 2023 Understanding Representation Learnability of Nonlinear Self-Supervised Learning AAAI 2023 Understanding the Feature Norm for Out-of-Distribution Detection ICCV 2023 Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry NeurIPS 2023