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Found 4 papers, 2 papers with code
Robust Anomaly Detection for Particle Physics Using Multi-Background Representation Learning
Anomaly, or out-of-distribution, detection is a promising tool for aiding discoveries of new particles or processes in particle physics.
Don't blame Dataset Shift! Shortcut Learning due to Gradients and Cross Entropy
However, even when the stable feature determines the label in the training distribution and the shortcut does not provide any additional information, like in perception tasks, default-ERM still exhibits shortcut learning.
When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious Correlations
In machine learning, incorporating more data is often seen as a reliable strategy for improving model performance; this work challenges that notion by demonstrating that the addition of external datasets in many cases can hurt the resulting model's performance.
Doc2Dict: Information Extraction as Text Generation
Typically, information extraction (IE) requires a pipeline approach: first, a sequence labeling model is trained on manually annotated documents to extract relevant spans; then, when a new document arrives, a model predicts spans which are then post-processed and standardized to convert the information into a database entry.
