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Paper Citation Record · LEDGER

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

As of 7 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 2026-08-07T06:34:17.273281+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:a361f78355f8b9448a631e8703c8fdb70f9f8ecfeb98d1d78f64a39ad116aa9d

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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no resolver link, observed 2026-08-07T05:59:03.724818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:03.724818Z digest=sha256:86b0bec42e8d593845205063d3b6e9927a01fb6ac4604b8b8fb536f5d0a2127e

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=sha256:1501d7997a43dee499eb39fe90c7798c74258a85e69900825b69825a41de269a

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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no resolver link, observed 2026-08-07T05:59:04.132004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:04.132004Z digest=sha256:57096951606eebf01c37f0be4077866d811456211045fadfc92152b28ffe1803

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:04.269861Z digest=sha256:63f72109fffcb9d95782bc83a98c770337b06b4c044c05a8232bd1690dbf9f6f

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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no resolver link, observed 2026-08-07T05:59:04.390203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:04.390203Z digest=sha256:01c7e8dd224a093c09cc3d4a40cf7ec8cd5454ef2c601c6e5b52e611df19634a

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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no resolver link, observed 2026-08-07T05:59:04.477301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:04.477301Z digest=sha256:538248bae13aef210fefb1c267c01178f48666841de24d24bcb8483cb69cdde3

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:04.589837Z digest=sha256:4fba8d946b3d69ae78072edff4fb52f6456d0db1e5f78390a053dcb22b677b49

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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no resolver link, observed 2026-08-07T05:59:04.714714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:04.714714Z digest=sha256:3fa09a49a06908b7db9ccd80b8e16487a830d191913878429a888acc3cc7e111

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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no resolver link, observed 2026-08-07T05:59:04.807050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:04.807050Z digest=sha256:c543bca22ad7a519dab8d46887d46cff521e50c4592e3dd3ed0d2d29ec877599

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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unresolved
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=sha256:6fcbfe4ada8d976f4699e7752dae09f0b0a96325147c76e0938e0b3f543b5b99

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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no resolver link, observed 2026-08-07T05:59:03.943693Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:03.943693Z digest=sha256:2e16da4909936d0d5f00abff145178b68a4b4d968350a5f1e8a89035abd8f0a7

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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no resolver link, observed 2026-08-07T05:59:03.328803Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:03.328803Z digest=sha256:07b1b52525732cec6d03ced613cc6a4c1d47ce9c8478499d88b0a2f5e3356de9

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:bcf50327763871f3e9cf750dd14d9e6985d9bd9fd66ecc58642a2d447f7da807

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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no resolver link, observed 2026-08-07T05:59:02.928475Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:02.928475Z digest=sha256:cf157c9e7c5b81b207842f805cd55615f107c1064baa2f89cda6a2c04a738508

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:59:03.565487Z digest=sha256:0e16610a71d7b19bec6329a71c8726c64bac74aee2f5941853d2f9c438f31b1b

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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no resolver link, observed 2026-08-07T05:59:03.050740Z

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source=pdf_text observed=2026-08-07T05:59:03.050740Z digest=sha256:f81fe3bb4a04ae99a2fa47959268ebabc127e2cdc891cb060478f0a71be650fa

Pith citing papers

No inbound Pith citation observations are available.