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Paper Citation Record · LEDGER

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms

As of 8 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2506.06499.

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

pith.paper-citation-record.v1
2506.06499 v2

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:59:04.914665Z

measured 17 of 17 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 636b0f40-d2ce-4b00-a687-2fa29576a052 · outbound

This paper cites STP: Self-play LLM Theorem Provers with Iterative Conjecturing and Proving.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms STP: Self-play LLM Theorem Provers with Iterative Conjecturing and Proving

Reference 3

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no resolver link, observed 2026-08-07T05:59:03.191174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:03.191174Z digest=sha256:cbff48b937cb9a240f5a272b83225fd867a56ca9eb853ef920af384a0b6794c5

Observation 05c392de-edbb-4834-8ecd-65d6c2389b0d · outbound

This paper cites Augmenting Math Word Problems via Iterative Question Composing.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms Augmenting Math Word Problems via Iterative Question Composing

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:03.724818Z digest=sha256:73a330ae2f2a4d12fa146c3204fceb5dcdde6d1d676a44af06dbe8480c22f98e

Observation f6f9f615-4df2-4ade-ac70-4f1c89bed220 · outbound

This paper cites WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct

Reference 8

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no resolver link, observed 2026-08-07T05:59:03.833516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:03.833516Z digest=sha256:ee5cda55f51f47e25947aa90f215ec18559a5d080e520960a4577f10fafa718d

Observation 2f318d3f-311a-42fc-b0c6-adc8c5eaff64 · outbound

This paper cites Learning Formal Mathematics From Intrinsic Motivation.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms Learning Formal Mathematics From Intrinsic Motivation

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:04.132004Z digest=sha256:f094316afcc8c50eb33565b9ac9adad6dde7cf853f953e3f796b1867982fc07c

Observation 96ed1b80-d670-428a-949e-227280c07d61 · outbound

This paper cites Mikayel Samvelyan, Sharath Chandra Raparthy, Andrei Lupu, Eric Hambro, Aram H.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms Mikayel Samvelyan, Sharath Chandra Raparthy, Andrei Lupu, Eric Hambro, Aram H

Reference 11

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no resolver link, observed 2026-08-07T05:59:04.269861Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:04.269861Z digest=sha256:c8364eab89801bec7c3de0480b1969059137e2d37804733ac2dd29f02e467f92

Observation e5e4dfcb-47a4-4f45-a5dd-578774dff898 · outbound

This paper cites Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:04.390203Z digest=sha256:2e30edfc790ba56f4ce84430a304895a8f7c376e1fb2e44dc89ce98e6b3879e7

Observation 53401402-b337-47e6-821e-4f5a5ca25942 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms Gemma 2: Improving Open Language Models at a Practical Size

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:04.477301Z digest=sha256:ac99de7bd866b4957efc472b490683b8744697aa103f12db23803a1bfa3563d0

Observation a2efa990-e530-4441-92b9-f9d0df2450d4 · outbound

This paper cites Open-Ended Learning Leads to Generally Capable Agents.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms Open-Ended Learning Leads to Generally Capable Agents

Reference 14

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no resolver link, observed 2026-08-07T05:59:04.589837Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:04.589837Z digest=sha256:c22ffd7e70050501ba2ba4f7d0119cef3b48305927c9848dccdcd85e4eb7bed1

Observation 79b9410f-4f44-4246-ae22-176812a71ed7 · outbound

This paper cites Evolutionary Computation in the Era of Large Language Model: Survey and Roadmap.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms Evolutionary Computation in the Era of Large Language Model: Survey and Roadmap

Reference 15

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:04.714714Z digest=sha256:e3ad875108073562ea7e401c0999594e4f00855c66a6c08913c29a3a4b6bfb73

Observation ba525dda-4628-4a8f-affa-26c74f75d3d0 · outbound

This paper cites MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models

Reference 16

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:04.807050Z digest=sha256:12179c7cead1f3ef99a177985ee0436447b4de5a9f4d032ce5e97fbb5384096e

Observation 71bb15fe-d816-4bc2-a8f1-9796d2593bc7 · outbound

This paper cites MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning

Reference 17

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no resolver link, observed 2026-08-07T05:59:04.914665Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:04.914665Z digest=sha256:f9190f9afa4ef18e9a1a7c04ba20907682c30ba4c16707a44bb4685f33c108b4

Observation b955b01e-2d9b-4eb3-b853-192167374063 · outbound

This paper cites Illuminating search spaces by mapping elites.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms Illuminating search spaces by mapping elites

Reference 2015

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:03.943693Z digest=sha256:6aa8119024b204becbdf8827689d667ed36fb53fb70ac783f39fd3804cb0d27a

Observation a70bfe7f-3d3b-4ea5-9228-8126eb576d70 · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms Measuring Mathematical Problem Solving With the MATH Dataset

Reference 2021

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source=pdf_text observed=2026-08-07T05:59:03.328803Z digest=sha256:adb5a1d5682518bd7bc78f19bb8fb5032c258539f26ea8484c5625e8b6cfb1e6

Observation def2b7f9-068a-4483-a1d2-375dc17bdce1 · outbound

This paper cites Evolution through Large Models.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms Evolution through Large Models

Reference 2022

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source=pdf_text observed=2026-08-07T05:59:03.428683Z digest=sha256:b1d3bb576b0b91add6c4a97a707e8176b472158b1691fc4b8d53af2d54a00c4d

Observation 87d472b8-c768-4763-8e56-8f388bf7b4d1 · outbound

This paper cites Quality-Diversity through AI Feedback.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms Quality-Diversity through AI Feedback

Reference 2023

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source=pdf_text observed=2026-08-07T05:59:02.928475Z digest=sha256:edf24727fb9b75044e8bac673039f2d95bc0a5a7831a65acb2cb4439482a99fc

Observation 66494c96-ae4b-47ff-92a2-624763c5b192 · outbound

This paper cites MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning

Reference 2024

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no resolver link, observed 2026-08-07T05:59:03.565487Z

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source=pdf_text observed=2026-08-07T05:59:03.565487Z digest=sha256:a30e50cefa8f24e1499ada94be3620c0fb675373317fbd3b827c9a50b7a7e97a

Observation 93bcd540-c87d-4052-ad87-619049e3ec72 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

SPARQ: Synthetic Problem Generation for Reasoning via Quality-Diversity Algorithms DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2025

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source=pdf_text observed=2026-08-07T05:59:03.050740Z digest=sha256:5af443db04e131ec2822f635033d84bdc48c4d391c460ffb50c20b2a8492b48b

Pith citing papers

No inbound Pith citation observations are available.