Papers by Xingjian Dong
Out-of-Distribution Detection through Soft Clustering with Non-Negative Kernel Regression (2024.findings-emnlp)
Copied to clipboard
| Challenge: | Existing methods for detecting out-of-distribution data are computationally complex and storage-intensive. |
| Approach: | They propose a soft clustering approach for OOD detection based on non-negative kernel regression . their approach greatly reduces computational and space complexities while retaining competitive performance. |
| Outcome: | The proposed approach outperforms existing methods by up to 4 AUROC points on four benchmarks while retaining competitive performance. |