SPECTRA generates reproducible synthetic IR corpora up to 60,000 documents with controllable distractors, long-tail vocabulary, and graded relevance labels via a single-process Python prototype.
Efficient generation and simulation of synthetic text corpora for scalable information retrieval testing,
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SEMBridge uses a tagless-final interface in a Python prototype to derive executable state transformers and verification conditions from the same loop-free imperative program definitions, tested on five examples up to 729 states.
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SPECTRA: Synthetic IR Test Collections with Relevance Oracles and Controlled Distractor Diagnostics
SPECTRA generates reproducible synthetic IR corpora up to 60,000 documents with controllable distractors, long-tail vocabulary, and graded relevance labels via a single-process Python prototype.
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SEMBridge: Tagless-Final Program Semantics with Weakest-Precondition and Bounded-Checking Interpretations
SEMBridge uses a tagless-final interface in a Python prototype to derive executable state transformers and verification conditions from the same loop-free imperative program definitions, tested on five examples up to 729 states.