Papers with data-driven partitioning
Similarity-Distance-Magnitude Activations (2026.findings-acl)
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| Challenge: | Existing methods for interpreting neural network-based language models (LMs) are limited to approximately conditional quantities. |
| Approach: | They introduce a similarity-distance-magnitude activation function and an SDM estimator to control class- and prediction-conditional accuracy among selective classifications. |
| Outcome: | The proposed estimator is more robust to covariate shifts and out-of-distribution inputs while remaining informative over in-difference data. |