Citation notice #7272 · 2026-07-11 11:51:00.273311+00:00

AutoOR: Scalably Post-training LLMs to Autoformalize Operations Research Problems

cites Small-Scale Shear Layers in Isotropic Turbulence of Viscoelastic Fluids, which carries a correction notice dated 2025-07-04. One-hop deterministic notice: the citation edge exists in the Pith bibliography graph; no model judged whether the citation was load-bearing.

This is not a judgment on the citing paper.

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01Evidence

Raw extraction · citation context · bibliography index 11

isting synthetic datasets suffer from low accuracy or are distilled from stronger models, making them expensive and difficult to scale [9, 10]. At the same time, the organizations that most need automated formalization, such as manufacturers or logistics operators, often have domain-specific problem distributions that are private and limited in size [11]. A practical system must therefore be able to start from a small set of representative problems, scale up verified training signal, and generalize without relying on human annotation or distillation. We present AutoOR, a scalable synthetic data generation and reinforcement learning pipeline that trains LLMs to autoformalize optimization problems across linear, mixed-integer, and non-

02Event

Type

Correction

Source

Crossref

Original DOI

10.1017/jfm.2024.1233

Notice DOI

10.1017/jfm.2025.341

Date

2025-07-04

Title

Small-scale shear layers in isotropic turbulence of viscoelastic fluids – ERRATUM

Reasons

['Correction']

Work

Small-Scale Shear Layers in Isotropic Turbulence of Viscoelastic Fluids (2025) Journal of Fluid Mechanics

Schema constants (for re-runners): correction · crossref

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