Paper Citation Record · LEDGER

Does Prompt Design Impact Quality of Data Imputation by LLMs?

As of 15 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 2 inbound Pith citation observations for arXiv:2506.04172.

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

pith.paper-citation-record.v1
2506.04172 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:50:50.204155Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T22:18:45.189576Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T14:05:46.733789Z

Reference resolution

29 of 29 outbound references displayed

verified exact2
verified fuzzy6
unresolved21
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ec0a6069-a38e-4454-a795-aae377807103 · outbound

This paper cites , " * write output.state after.block = add.period write newline.

Does Prompt Design Impact Quality of Data Imputation by LLMs? , " * write output.state after.block = add.period write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T10:50:50.032299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70bb04c9-6eea-48cf-8d04-3593f84d9148 · outbound

This paper cites write newline.

Does Prompt Design Impact Quality of Data Imputation by LLMs? write newline

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T10:50:50.047629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d3c0fca-f2b6-42fc-a739-0c4b66ab7241 · outbound

This paper cites an unresolved cited work.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:50:51.044304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 45d5f491-44c9-43cf-a3fa-5123bf39a4ca · outbound

This paper cites Language Models are Realistic Tabular Data Generators.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Language Models are Realistic Tabular Data Generators

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T10:50:50.077250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae07147a-c580-479b-8290-b20f3d232e5d · outbound

This paper cites D.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; et al.

Does Prompt Design Impact Quality of Data Imputation by LLMs? D.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; et al

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:50:51.034483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3aa2da86-37f4-4309-a26f-01818562f8dc · outbound

This paper cites V.; Bowyer, K.

Does Prompt Design Impact Quality of Data Imputation by LLMs? V.; Bowyer, K

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:50:51.024544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9bf39cd0-0b27-49cc-810e-b9d0192ae613 · outbound

This paper cites an unresolved cited work.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:50:51.013332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9af770bd-b95f-4e9c-8262-fc4b0685bab7 · outbound

This paper cites an unresolved cited work.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:50:51.003185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 50ac4fec-efb6-4007-bb58-ff71a980fa52 · outbound

This paper cites an unresolved cited work.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:50:50.991877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 129ef3b9-68a8-4fee-b771-bc6ddc92269d · outbound

This paper cites an unresolved cited work.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:50:50.982718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bd74eb56-5e7d-4031-bf7a-3a93ccf39aff · outbound

This paper cites an unresolved cited work.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:50:50.969812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ff266c60-fd7f-4f17-be12-b9326f88f34a · outbound

This paper cites Enhancing Robustness in Large Language Models: Prompting for Mitigating the Impact of Irrelevant Information.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Enhancing Robustness in Large Language Models: Prompting for Mitigating the Impact of Irrelevant Information

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T10:50:50.123055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28bd1275-bfa1-4d66-957c-8d336f77f2c1 · outbound

This paper cites B.; Girard, P.; and Terranova, N.

Does Prompt Design Impact Quality of Data Imputation by LLMs? B.; Girard, P.; and Terranova, N

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:50:50.957109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9871a274-0bc3-4a8f-87d5-97519f3cd386 · outbound

This paper cites END: Early Noise Dropping for Efficient and Effective Context Denoising.

Does Prompt Design Impact Quality of Data Imputation by LLMs? END: Early Noise Dropping for Efficient and Effective Context Denoising

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:50:50.653326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6d070720-1e26-4155-8f14-c2fe9abe2818 · outbound

This paper cites an unresolved cited work.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:50:50.946268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation be059cc8-cfd3-450f-9e58-5fa947c01a48 · outbound

This paper cites an unresolved cited work.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:50:50.934827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3396e394-2f40-44ee-987b-c6873c83bfa5 · outbound

This paper cites Auto-Encoding Variational Bayes.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Auto-Encoding Variational Bayes

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T10:50:50.144350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b045b58-0332-4d04-af85-8e7d47de0eed · outbound

This paper cites S.; Reid, M.; Matsuo, Y.; and Iwasawa, Y.

Does Prompt Design Impact Quality of Data Imputation by LLMs? S.; Reid, M.; Matsuo, Y.; and Iwasawa, Y

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:50:50.922744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2fc26267-2a43-45f5-b813-776633838bc8 · outbound

This paper cites Data Generation Using Large Language Models for Text Classification: An Empirical Case Study.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Data Generation Using Large Language Models for Text Classification: An Empirical Case Study

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T10:50:50.153342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03d7a2d4-33e7-4be3-bc8f-9f1c87f87286 · outbound

This paper cites Best Practices and Lessons Learned on Synthetic Data.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Best Practices and Lessons Learned on Synthetic Data

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T10:50:50.157269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bab40330-8c93-4715-950b-a85c840ea0ef · outbound

This paper cites On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey.

Does Prompt Design Impact Quality of Data Imputation by LLMs? On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T10:50:50.163370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 918a8530-ca52-4f34-97d8-d8973baa339b · outbound

This paper cites an unresolved cited work.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Unresolved cited work

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T10:50:50.168787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d41c2700-d16f-4da0-8cea-b4c3faba6e49 · outbound

This paper cites Data Synthesis based on Generative Adversarial Networks.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Data Synthesis based on Generative Adversarial Networks

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T10:50:50.172662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40b31283-d2a8-471c-b342-ee72244dfc02 · outbound

This paper cites H.; Sch \"a rli, N.; and Zhou, D.

Does Prompt Design Impact Quality of Data Imputation by LLMs? H.; Sch \"a rli, N.; and Zhou, D

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:50:50.912789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e77165e8-c892-4ae5-958a-f902cadf9198 · outbound

This paper cites V.; Zhou, D.; et al.

Does Prompt Design Impact Quality of Data Imputation by LLMs? V.; Zhou, D.; et al

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T10:50:50.180831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d396899b-b2c9-42e8-a9ef-14d72ae4ccbd · outbound

This paper cites an unresolved cited work.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:50:50.900620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d12b3dd1-1b1b-4904-9c6e-47d0db4b00c2 · outbound

This paper cites J.; Krishna, R.; Shen, J.; and Zhang, C.

Does Prompt Design Impact Quality of Data Imputation by LLMs? J.; Krishna, R.; Shen, J.; and Zhang, C

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:50:50.867486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3cec156f-e529-41ae-98f2-827691a458ce · outbound

This paper cites ReGen: Zero-Shot Text Classification via Training Data Generation with Progressive Dense Retrieval.

Does Prompt Design Impact Quality of Data Imputation by LLMs? ReGen: Zero-Shot Text Classification via Training Data Generation with Progressive Dense Retrieval

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-07T10:50:50.345359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9cc7e790-e9b8-4b4e-a61e-8c0438af1583 · outbound

This paper cites Large Language Models Are Human-Level Prompt Engineers.

Does Prompt Design Impact Quality of Data Imputation by LLMs? Large Language Models Are Human-Level Prompt Engineers

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T10:50:50.204155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation adc26130-5916-4e95-8611-86ee7d5a1a6c · inbound

ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows cites this paper.

ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows Does Prompt Design Impact Quality of Data Imputation by LLMs?

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:57:22.517689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f33e58be-df65-42af-999e-ff20d7f3f35e · inbound

ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows cites this paper.

ProfiliTable: Profiling-Driven Tabular Data Processing via Agentic Workflows Does Prompt Design Impact Quality of Data Imputation by LLMs?

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:05:46.735213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.