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Fast list recovery of univariate multiplicity and folded Reed-Solomon codes

Published: November 28, 2025 | arXiv ID: 2512.00248v1

By: Rohan Goyal , Prahladh Harsha , Mrinal Kumar and more

BigTech Affiliations: Massachusetts Institute of Technology

Potential Business Impact:

Recovers lost data from corrupted messages faster.

Business Areas:
QR Codes Software

A recent work of Goyal, Harsha, Kumar and Shankar gave nearly linear time algorithms for the list decoding of Folded Reed-Solomon codes (FRS) and univariate multiplicity codes up to list decoding capacity in their natural setting of parameters. A curious aspect of this work was that unlike most list decoding algorithms for codes that also naturally extend to the problem of list recovery, the algorithm in the work of Goyal et al. seemed to be crucially tied to the problem of list decoding. In particular, it wasn't clear if their algorithm could be generalized to solve the problem of list recovery FRS and univariate multiplicity codes in near linear time. In this work, we address this question and design $\tilde{O}(n)$-time algorithms for list recovery of Folded Reed-Solomon codes and univariate Multiplicity codes up to capacity, where $n$ is the blocklength of the code. For our proof, we build upon the lattice based ideas crucially used by Goyal et al. with one additional technical ingredient - we show the construction of appropriately structured lattices over the univariate polynomial ring that \emph{capture} the list recovery problem for these codes.

Country of Origin
🇺🇸 United States

Page Count
21 pages

Category
Computer Science:
Information Theory