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Paper Citation Record · LEDGER

OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2407.09887.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2407.09887 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T20:55:41.446307Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T20:20:07.316705Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 73bc69c2-e1d9-476b-81b4-8449ee6923b3 · inbound

A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solving cites this paper.

A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solving OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-04T20:55:41.446307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T20:55:41.446307Z digest=sha256:d2fdbc7ea93d6f500ae6497ae046391bfa4006fc6a2872daf0104c1dd25bc3f7

Observation e7d068cc-1a9a-43b8-a591-df90929808b5 · inbound

OPT-Engine: Benchmarking the Limits of LLMs in Optimization Modeling via Complexity Scaling cites this paper.

OPT-Engine: Benchmarking the Limits of LLMs in Optimization Modeling via Complexity Scaling OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-16T16:18:05.390439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T16:17:43.055124Z digest=sha256:5a55e510522bc6475cf0f9811fb4c0685c0f3fb951e1e2dc608ac7ebd58048d3

Observation 7e44d329-8889-42bf-9d87-644fc7c5d0c0 · inbound

AutoOR: Scalably Post-training LLMs to Autoformalize Operations Research Problems cites this paper.

AutoOR: Scalably Post-training LLMs to Autoformalize Operations Research Problems OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-10T07:11:53.576185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T07:02:02.992871Z digest=sha256:7967f5c4f87cba121cc579d720f3985bc0de82b33feb8d42aa0a19e06717d9a4

Observation 67128f47-78f5-4abb-97ff-8a3978a444e6 · inbound

Co-evolving Agent Architectures and Interpretable Reasoning for Automated Optimization cites this paper.

Co-evolving Agent Architectures and Interpretable Reasoning for Automated Optimization OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

Reference 95

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:23:37.819052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-10T05:21:51.915690Z digest=sha256:49f0010876e8b438241f48e3cc6fe3859d604e6ec90883b041ac4e996b1b5221

Observation a37fc80e-4bc3-4a19-937e-889762681210 · inbound

From Soliloquy to Agora: Memory-Enhanced LLM Agents with Decentralized Debate for Optimization Modeling cites this paper.

From Soliloquy to Agora: Memory-Enhanced LLM Agents with Decentralized Debate for Optimization Modeling OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

Reference 25

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T00:06:18.414297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T15:47:28.474020Z digest=sha256:43b70d8e406d9a6235bc62ef1b5c25c3c27cc1b11d6f9af412c7cfdbbeee2a98

Observation b25d43f2-82bf-4f79-bd8a-7c4133441bdf · inbound

FrontierOR: Benchmarking LLMs' Capacity for Efficient Algorithm Design in Large-Scale Optimization cites this paper.

FrontierOR: Benchmarking LLMs' Capacity for Efficient Algorithm Design in Large-Scale Optimization OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-07-01T16:35:50.672044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T00:27:22.908863Z digest=sha256:4e4d62d40578d4c73b32f6e4b064d08e9728cfeef17796ec16f99d224f396c00

Observation 04c8868b-58ee-4aec-9c39-ba4e6cc12d13 · inbound

Generating Robust Portfolios of Optimization Models using Large Language Models cites this paper.

Generating Robust Portfolios of Optimization Models using Large Language Models OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-06-29T16:53:40.874378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T16:48:44.853164Z digest=sha256:40330c8948058ff79a3a351e146c1d4ca0a44c1847737be27b3f3634716f3671

Observation 1ee6f713-861a-4418-8299-c541dbca3b29 · inbound

MiniOpt: Reasoning to Model and Solve General Optimization Problems with Limited Resources cites this paper.

MiniOpt: Reasoning to Model and Solve General Optimization Problems with Limited Resources OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-07-04T20:20:07.318482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-25T20:19:30.720291Z digest=sha256:93d5005e004371161c1a5906f99f3cfd4ad3ededb3e94379f559c39766aa3dbe

Observation f6de65e3-5066-4294-a85b-5f8ce43c2dbc · inbound

MiniOpt: Reasoning to Model and Solve General Optimization Problems with Limited Resources cites this paper.

MiniOpt: Reasoning to Model and Solve General Optimization Problems with Limited Resources OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:19:50.717600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T05:18:55.074710Z digest=sha256:9816a22ff5581f91f634c855f0c0a0f8de4e1b4e5c6dd0e9d80bd750b0f0da1e

Observation 6e2f6da4-456b-4678-bd28-6e041765755b · inbound

A$^{2}$utoLPBench: An Auto-Generated, Agent-Friendly LP Benchmark via Inverse-KKT Construction cites this paper.

A$^{2}$utoLPBench: An Auto-Generated, Agent-Friendly LP Benchmark via Inverse-KKT Construction OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-07-03T14:18:22.642292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-07-03T14:08:50.462880Z digest=sha256:1f64336703c08deb125badc24954603d42f3ef139ab8ae1dfd83657e7b8b3c42

Observation 04db4152-1814-48db-8c98-21a30dd27b64 · inbound

Falsification-Based Verification of LLM-Generated Optimization Models: Sound Test Batteries and Their Detection Limits cites this paper.

Falsification-Based Verification of LLM-Generated Optimization Models: Sound Test Batteries and Their Detection Limits OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-01T20:26:11.422946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T20:26:11.422946Z digest=sha256:974f24a4131d09e45261bf7f5dca7c52c03268070ebd8faea95080c8494d539c

Observation ad45008e-8614-498b-8813-eae2c1780ddb · inbound

PEARL: Solver-in-the-Loop Interactive Optimization Modeling from Natural Language cites this paper.

PEARL: Solver-in-the-Loop Interactive Optimization Modeling from Natural Language OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-02T14:04:55.806898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T14:04:55.806898Z digest=sha256:02a1995c1cbaec3e79137bea36bb103cbf27f4d724fa60903cf06882b29a7594

Observation 533ab34f-2727-4fa5-9589-bb3884ec6e32 · inbound

Search Hardness-Aware LLM-Based Problem Formulation for Expensive Simulation-Driven Design cites this paper.

Search Hardness-Aware LLM-Based Problem Formulation for Expensive Simulation-Driven Design OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-01T08:09:49.393810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T08:09:49.393810Z digest=sha256:62c2d8d05f65ccbd765c322bd1461cc2b1943289171431a2e3c63d53b29fa8d1

Observation afa62ad4-3ee9-44f0-84c9-8ea21c26c2f6 · inbound

Uncertainty-Aware Simulation-Based Inference for Operations Research with Large Language Models cites this paper.

Uncertainty-Aware Simulation-Based Inference for Operations Research with Large Language Models OptiBench Meets ReSocratic: Measure and Improve LLMs for Optimization Modeling

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-04T02:03:06.898647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T02:03:06.898647Z digest=sha256:ab0e3fe79514e33edb86cdec7448279cad8049ec638edcee94b6e0b2cfd016cf