Paper Citation Record · LEDGER

Using Large Language Models for Idea Generation in Innovation

As of 9 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2607.27553.

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

pith.paper-citation-record.v1
2607.27553 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T05:52:35.096351Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

12 of 12 outbound references displayed

verified exact0
verified fuzzy0
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7f5f0284-d84c-4303-b8db-2bdcc06b3794 · outbound

This paper cites an unresolved cited work.

Using Large Language Models for Idea Generation in Innovation Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T05:52:33.309212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3ce1bb6-7233-4c7f-b674-69cd6a2e0b7e · outbound

This paper cites Delving into LLM-assisted writing in biomedical publications through excess vocabulary.

Using Large Language Models for Idea Generation in Innovation Delving into LLM-assisted writing in biomedical publications through excess vocabulary

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T05:52:33.707168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 382d19b4-f7d8-41a6-9654-d49e98aba34c · outbound

This paper cites GPT-4 Technical Report.

Using Large Language Models for Idea Generation in Innovation GPT-4 Technical Report

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T05:52:34.278735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f2756fc-7215-4958-a4ca-cdc85e6f807d · outbound

This paper cites Siangliulue P, Chan J, Dow SP, Gajos KZ (2016) IdeaHound: Improving Large-scale Collaborative Ideation with Crowd-Powered Real-time Semantic Modeling.

Using Large Language Models for Idea Generation in Innovation Siangliulue P, Chan J, Dow SP, Gajos KZ (2016) IdeaHound: Improving Large-scale Collaborative Ideation with Crowd-Powered Real-time Semantic Modeling

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T05:52:34.421080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7406c751-36c6-43c6-98f5-861d1bb99641 · outbound

This paper cites GPT-who: An Information Density-based Machine-Generated Text Detector.

Using Large Language Models for Idea Generation in Innovation GPT-who: An Information Density-based Machine-Generated Text Detector

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T05:52:34.759156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c23fad6b-b16b-4212-89a4-746de0fe3b2a · outbound

This paper cites Terwiesch C, Ulrich K (2023) The innovation tournament handbook: a step-by-step guide to finding exceptional solutions to any challenge (Wharton School Press, Philadelphia, PA).

Using Large Language Models for Idea Generation in Innovation Terwiesch C, Ulrich K (2023) The innovation tournament handbook: a step-by-step guide to finding exceptional solutions to any challenge (Wharton School Press, Philadelphia, PA)

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T05:52:34.590182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 061c1146-1e7a-4718-aeb0-71bb471a8dc7 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Using Large Language Models for Idea Generation in Innovation Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T05:52:35.096351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b175d4c-fea9-41c0-baef-9140eebf6abe · outbound

This paper cites Doshi AR, Hauser OP (2024) Generative AI enhances individual creativity but reduces the collective diversity of novel content.

Using Large Language Models for Idea Generation in Innovation Doshi AR, Hauser OP (2024) Generative AI enhances individual creativity but reduces the collective diversity of novel content

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T05:52:33.548905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e896bfe-a288-4f91-abd4-1ff9651a84c9 · outbound

This paper cites Language Models are Few-Shot Learners.

Using Large Language Models for Idea Generation in Innovation Language Models are Few-Shot Learners

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T05:52:33.435282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c11bbb12-9689-454f-a163-6b01c269fe99 · outbound

This paper cites DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature.

Using Large Language Models for Idea Generation in Innovation DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T05:52:33.866286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88527231-3b42-4729-9964-82aa5bb33564 · outbound

This paper cites Can AI Be as Creative as Humans?.

Using Large Language Models for Idea Generation in Innovation Can AI Be as Creative as Humans?

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T05:52:34.934309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14620fe8-e808-4373-b4fd-6828fb831bb4 · outbound

This paper cites OpenAI, Achiam J, Adler S, Agarwal S, Ahmad L, Akkaya I, Aleman FL, et al.

Using Large Language Models for Idea Generation in Innovation OpenAI, Achiam J, Adler S, Agarwal S, Ahmad L, Akkaya I, Aleman FL, et al

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T05:52:34.037646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.