Latest Research in Domain Adaptation and Few-Shot Learning

Top Research Topics in Domain Adaptation and Few-Shot Learning

• Computer Vision and Pattern Recognition — 56 papers
• Machine Learning — 20 papers
• Artificial Intelligence — 3 papers
• Domain Adaptation and Few-Shot Learning — 2 papers
• Advanced Neural Network Applications — 2 papers
• Adversarial Robustness in Machine Learning — 1 papers
• Neural and Evolutionary Computing — 1 papers
• Cryptography and Security — 1 papers
• Generative Adversarial Networks and Image Synthesis — 1 papers
• Model Reduction and Neural Networks — 1 papers

Highest-Cited Papers

1. Limits of Confidence in Diffusion
2. Multi-Axis Max@K Reinforcement Learning for Representative Diversity in Text-to-Image Generation
3. Rethinking the Design Space of Reinforcement Learning for Diffusion Models: On the Importance of Likelihood Estimation Beyond Loss Design
4. Riemannian--Lorentz Fusion of Vision Transformers and State-Space Models
5. Ambient Dataloops: Generative Models for Dataset Refinement
6. PiPS: Post-Hoc Prototypical Explanations for Interpretable Semantic Segmentation
7. Channel-Wise and Token-Aware Post-Training Quantization for Visual State Space Duality
8. Vision-language sample scoring with dynamic coverage-centric strategies
9. Qwen-Image-Flash: Rethinking the Training Recipe for Few-Step Distillation
10. Principal-timestep Restricted Init via Sparse Matrix-decomposition in Flow-matching
11. How Do Video Foundation Models Encode Intuitive Physics? Probing Across Pretraining Paradigms
12. Flow Duality and Source Geometry for Categorical Generation
13. Mutual Learning across heterogeneous architectures for image classification
14. Same Encoder, Different Winner: A Paired-View Framework for Cell Painting Encoder Evaluation
15. GRACE: Adaptive Concept Erasure with Geometry-Guided Retention in Diffusion Models
16. ReCAST: Reward Credit Assignment across Timesteps for Online Diffusion Reinforcement
17. Diffusion Models and Concept Formation
18. What Transfers and What Collapses: A Cross-Generator Study of AI-Generated Image Detection with Corrected Evaluation
19. Smoothing the Score Function to Enhance Generalization in Diffusion Models
20. Logit Refiner: Improving Visual Autoregressive Models via Intra-Scale Dependency Modeling