One (Block) Size Fits All: PIR and SPIR with Variable-Length Records via Multi-Block Queries.
Why this work is in the frame
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Bibliographic record
Abstract
We propose a new, communication-efficient way for users to fetch multiple blocks simultaneously in Goldberg’s robust information-theoretic private information retrieval (IT-PIR) scheme. Our new multi-block IT-PIR trades off some Byzantine robustness to improve throughput without affecting user privacy. By taking advantage of the recent Cohn-Heninger multi-polynomial list decoding algorithm, we show how realistic parameter choices enable the user to retrieve several blocks without increasing the commu-nication or computation costs beyond what is required to retrieve a single block, and argue that the resulting scheme still maintains essentially optimal Byzantine robustness in practice. We also derive optimal parameters for our construction, which yields communication costs within a small factor of the lowest possible. With our new multi-block IT-PIR protocol as a starting point, we construct four new symmetric PIR (SPIR) protocols that each support variable-length database records. By decoupling the PIR block size from the lengths of individual database records, we are free to fix the block size to its communication-optimal value without artificially restricting the contents and layout of the records. Moreover, it is straightforward to augment three of our four new SPIR constructions with efficient zero-knowledge proofs about the particular records a user is requesting in a given query; this makes it easy to implement pricing and access control structures over the records using standard techniques from the literature. The resulting SPIR protocols are therefore well suited to privacy-preserving e-commerce applications, such as privacy-friendly sales of e-books, music, movies, or smart phone and tablet apps.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it