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Paper Citation Record · LEDGER

Synthetic Consumer Insight Generation with Large Language Models

As of 10 August 2026, this Paper Citation Record lists 5 of 5 outbound references and 0 inbound Pith citation observations for arXiv:2607.05761.

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

pith.paper-citation-record.v1
2607.05761 v1

Coverage vector

measured 5 of 5 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T02:22:45.862673Z

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

5 of 5 outbound references displayed

  • verified exact3
  • verified fuzzy0
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 44e353e1-a20c-4008-8d0a-4d710ad4c91d · outbound

This paper cites an unresolved cited work.

Synthetic Consumer Insight Generation with Large Language Models Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-07-11T02:27:50.413157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T02:22:45.862673Z digest=sha256:4ddb568865b9e239a1b283a418d510bad06d8d96982502f2c05aa5d7bda55010

Observation c2a36032-4b82-4c48-92a5-445426993370 · outbound

This paper cites Scaling Synthetic Data Creation with 1,000,000,000 Personas.

Synthetic Consumer Insight Generation with Large Language Models Scaling Synthetic Data Creation with 1,000,000,000 Personas

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-07-11T02:27:47.641300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T02:22:45.862673Z digest=sha256:0a17ffdb3e1e7261c5650eaed96dbd01698350c09bc731ac42959aea75a425e9

Observation 07946474-8b5b-475d-92d1-ce07f8a731ba · outbound

This paper cites The Curious Case of Neural Text Degeneration.

Synthetic Consumer Insight Generation with Large Language Models The Curious Case of Neural Text Degeneration

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-07-11T02:27:47.695216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T02:22:45.862673Z digest=sha256:73eab250963ed8edd6dc07e38619bfebf75822873f4a08a8782eb61b7ac4dff9

Observation b58efa20-1425-4456-a538-006d4ec3398b · outbound

This paper cites Large Language Model Routing with Benchmark Datasets.

Synthetic Consumer Insight Generation with Large Language Models Large Language Model Routing with Benchmark Datasets

Reference 4

Resolution
metadata mismatch
local_arxiv, observed 2026-07-11T02:27:47.667921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T02:22:45.862673Z digest=sha256:2d390021341bdaa9e0d5dbeeeb8d3d5f37584c969c05e029ede4032bddae69b6

Observation 5018278c-0554-4737-990c-b3c080f7dadf · outbound

This paper cites Does Synthetic Data Generation of LLMs Help Clinical Text Mining?.

Synthetic Consumer Insight Generation with Large Language Models Does Synthetic Data Generation of LLMs Help Clinical Text Mining?

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-07-11T02:27:47.717255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T02:22:45.862673Z digest=sha256:a822983e31b4b07ee6c167cc4a00b2d8defc4bd1989fe1819518631b1ef864d8

Pith citing papers

No inbound Pith citation observations are available.