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Record W4405504959 · doi:10.1145/3708508

Robustness for Space-Bounded Statistical Zero Knowledge

2024· article· en· W4405504959 on OpenAlexaff
Eric Allender, Jeremy C. Gray, Saachi Mutreja, Harsha Tirumala

Bibliographic record

VenueACM Transactions on Computation Theory · 2024
Typearticle
Languageen
FieldComputer Science
TopicDistributed Sensor Networks and Detection Algorithms
Canadian institutionsUniversity of Toronto
FundersSimons Institute for the Theory of Computing, University of California BerkeleyNational Science Foundation
KeywordsBounded functionRobustness (evolution)Zero-knowledge proofZero (linguistics)MathematicsDiscrete mathematicsComputer sciencePure mathematicsMathematical analysisAlgorithm

Abstract

fetched live from OpenAlex

We show that the space-bounded statistical zero knowledge classes SZK L and NISZK L are surprisingly robust, in that the power of the verifier and simulator can be strengthened or weakened without affecting the resulting class.Coupled with other recent characterizations of these classes [ 5 ], this can be viewed as lending support to the conjecture that these classes may coincide with the non-space-bounded classes SZK and NISZK , respectively.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.056
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.056
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.006
Scholarly communication0.0050.008
Open science0.0030.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.022
GPT teacher head0.295
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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Same venueACM Transactions on Computation TheorySame topicDistributed Sensor Networks and Detection AlgorithmsFrench-language works237,207