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Paper Citation Record · LEDGER

Auto-Drafting Police Reports from Noisy ASR Outputs: A Trust-Centered LLM Approach

As of 8 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 0 inbound Pith citation observations for arXiv:2502.07677.

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

pith.paper-citation-record.v1
2502.07677 v3

Coverage vector

measured 10 of 10 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:58:26.946663Z

measured 10 of 10 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

10 of 10 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 23c5726c-df83-43d7-a7e5-2ae7d89b805a · outbound

This paper cites an unresolved cited work.

Auto-Drafting Police Reports from Noisy ASR Outputs: A Trust-Centered LLM Approach Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-08T11:58:27.361603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T11:58:26.181603Z digest=sha256:ace8ea92325cc9e8ffe2b6bdd0b7a7e0b1616dc5908673c209d182c8384c74aa

Observation 625102da-a57a-4b9c-bbf3-5378875d2372 · outbound

This paper cites an unresolved cited work.

Auto-Drafting Police Reports from Noisy ASR Outputs: A Trust-Centered LLM Approach Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-08T11:58:27.350620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T11:58:26.552059Z digest=sha256:68f3d3574972272ef989cc4ab0befe05e669be9e7d3e7db4e99ece780760e6d2

Observation 429b2825-ece2-4e6b-b02e-84dcf218294a · outbound

This paper cites an unresolved cited work.

Auto-Drafting Police Reports from Noisy ASR Outputs: A Trust-Centered LLM Approach Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-08T11:58:27.334038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T11:58:26.692539Z digest=sha256:fe5c351ec95d962cb392ff01cf84750017b31dd4e4dcbf6e3e63cc763153fcaf

Observation 258d6b80-65f3-48bc-8571-362d2fe0d40c · outbound

This paper cites an unresolved cited work.

Auto-Drafting Police Reports from Noisy ASR Outputs: A Trust-Centered LLM Approach Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-08T11:58:27.317960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T11:58:26.777608Z digest=sha256:5dd19d076791169db0a7141d1330aa79612c492e3b20e68dcc9cbecfa4d77e5c

Observation c368bc1f-106a-4ed1-9037-8afdccb8df1e · outbound

This paper cites an unresolved cited work.

Auto-Drafting Police Reports from Noisy ASR Outputs: A Trust-Centered LLM Approach Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-08T11:58:27.293492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T11:58:26.879239Z digest=sha256:9d3f9ec291cb4a394ed7ec4e7116c4992b9b18e451545c39ebea639a59e69b35

Observation 464bc843-2f03-44bd-822c-b564bd27d0a4 · outbound

This paper cites an unresolved cited work.

Auto-Drafting Police Reports from Noisy ASR Outputs: A Trust-Centered LLM Approach Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-08T11:58:27.178894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T11:58:26.926186Z digest=sha256:79a6c4eebc51fd3a72f7ff40d87e2824501c633941670c7e24687a37c9cc4055

Observation 223ff027-8afe-4fc7-9d0e-dfb220a749b3 · outbound

This paper cites an unresolved cited work.

Auto-Drafting Police Reports from Noisy ASR Outputs: A Trust-Centered LLM Approach Unresolved cited work

Reference 7

Resolution
unresolved
raw_fallback, observed 2026-08-08T11:58:27.012161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T11:58:26.932938Z digest=sha256:4556d667200461ae1dc6f59b0392abec9514b987429b344ea720d5aa4057f121

Observation f0780a42-c059-4d2f-83f2-8555a4f6f439 · outbound

This paper cites an unresolved cited work.

Auto-Drafting Police Reports from Noisy ASR Outputs: A Trust-Centered LLM Approach Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-08T11:58:27.000195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-08T11:58:26.937363Z digest=sha256:92ff174000f23c94349eac2ef2b7ca8c7052b8fc2540287162b7f3becb06b256

Observation dd2e243e-ee8c-4ec6-af27-1c518936c248 · outbound

This paper cites Knowledge-Infused Legal Wisdom: Navigating LLM Consultation through the Lens of Diagnostics and Positive-Unlabeled Reinforcement Learning.

Auto-Drafting Police Reports from Noisy ASR Outputs: A Trust-Centered LLM Approach Knowledge-Infused Legal Wisdom: Navigating LLM Consultation through the Lens of Diagnostics and Positive-Unlabeled Reinforcement Learning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-08T11:58:26.942064Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:58:26.942064Z digest=sha256:56e310647e0520a474f271e77ca06ccb02f7d41a114f579bbd9d4fa6df479614

Observation 82e36069-78f3-48f8-acfb-240ebf682e40 · outbound

This paper cites Precedent-Enhanced Legal Judgment Prediction with LLM and Domain-Model Collaboration.

Auto-Drafting Police Reports from Noisy ASR Outputs: A Trust-Centered LLM Approach Precedent-Enhanced Legal Judgment Prediction with LLM and Domain-Model Collaboration

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-08T11:58:26.946663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:58:26.946663Z digest=sha256:cf467511f6e26da0417a4f9c46e1d31a5db871751b207705ce848e50c3c897e2

Pith citing papers

No inbound Pith citation observations are available.