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This work embeds a dataset's completions with Sentence-BERT, subtract the embeddings of clean reference completions, and compares the result to an open vocabulary of candidate topics, observing that different teacher models appear to express the same bias through different vocabulary.
DynSHAP is proposed, a SHAP framework suited specifically for dynamic survival analysis that learns linear dependencies in features over time and uses conditional sampling to address them in explanations, and Temporal DynSHAP, which learns linear dependencies in features over time and uses conditional sampling to addre...
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