Fractal Commitments Enable Universal Logarithmic-Size Verifiable Computation
This new fractal commitment scheme recursively compresses polynomial proofs, achieving truly logarithmic verification costs for universal computation without a trusted setup.
Subspace Codes Enable Logarithmic Proof Size Constant Verification Time Commitment
A novel polynomial commitment scheme using subspace codes achieves logarithmic proof size and constant verification, enhancing rollup efficiency.
HyperCommit Achieves Constant-Time Verifiable Data Availability Sampling
A novel polynomial commitment scheme enables light clients to verify massive data availability with constant-time cryptographic proofs, securing modular scaling.
FRIDA Enables Transparent Data Availability Sampling with Poly-Logarithmic Proofs
FRIDA uses a novel FRI-based commitment to achieve non-trusted setup data availability sampling, fundamentally improving scalability.
Nova Folding Scheme Enables Efficient Recursive Proof Accumulation
Nova's non-interactive folding scheme compresses arbitrary computation histories into a single, logarithmic-size proof, finally enabling practical IVC.
Folding Schemes Enable Fastest Recursive Zero-Knowledge Arguments
The Nova folding scheme dramatically accelerates verifiable computation by deferring all intermediate proof checks into a single, succinct final argument.
Logarithmic Zero-Knowledge Proofs Eliminate Trusted Setup for Private Computation
Bulletproofs introduce non-interactive zero-knowledge proofs with logarithmic size and no trusted setup, fundamentally solving the proof-size bottleneck for on-chain privacy.
Information-Theoretic State Compression Secures Distributed Ledger Integrity
This research introduces the State-Trellis structure, leveraging error-correcting codes to achieve constant-time, fixed-size state verification, fundamentally improving light client security.
Unified Framework Achieves Private Scalable Verifiable Machine Learning
The new proof-composition framework casts verifiable machine learning as succinct matrix computations, delivering linear prover time and architecture privacy for decentralized AI.
