X account: 1/ Hash-based SNARK proofs are hundreds of KB, too large for many applications. Researchers hoped to halve their size using unproven conjectures. Our new paper rules out this route for binary-field SNARKs. With @QuangVDao @skominers @kaizhengcs https://t.co/6JQI2plaKx
X account @succinctjt named that a new paper with collaborators argues that the size of binary-field hash-based SNARK proofs cannot be halved through the previously hypothesized unproven conjecture.
Article
1/ Hash-based SNARK proofs are hundreds of KB, too large for many applications. Researchers hoped to halve their size using unproven conjectures. Our new paper rules out this route for binary-field SNARKs.
With @QuangVDao @skominers @kaizhengcs
https://t.co/6JQI2plaKx
Key points
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1/ Hash-based SNARK proofs are hundreds of KB, too large for many applications. Researchers hoped to halve their size using unproven conjectures. Our new paper rules out this route for binary-field SNARKs.
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With @QuangVDao @skominers @kaizhengcs
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https://t.co/6JQI2plaKx
AI-assisted interpretation
The following is analysis, separate from reported facts. Verify important claims independently.
Zero-knowledge proofs and binary-field SNARK ecosystem: If the paper's conclusion holds, research and product design relying on this proof-size compression approach will need to be adjusted, potentially limiting some application designs sensitive to proof size.
Why it matters to readers
The information comes from researcher X's post, which includes a paper link, but the supplied material does not contain the paper's content or independent verification, so the applicability and rigor of the technical conclusion cannot be confirmed.
Subject of focus: zero-knowledge proofs and binary-field SNARK ecosystem. Observation period: medium to long term
Risks and unknowns
Validation of the conclusion and conditions of applicability through the full paper and peer review
Relevant SNARK Whether the relevant project explains that its technical approach is affected
Whether alternative proof-compression solutions emerge
Zero-knowledge proofs and binary-field SNARK Reverse conditions for assessing ecosystem impact: the paper is found to contain errors, the conclusion has a limited scope of applicability, or another feasible proof-compression method emerges.