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Paper Citation Record · LEDGER

Truthful AI: Developing and governing AI that does not lie

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2110.06674.

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

pith.paper-citation-record.v1
2110.06674 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T14:50:24.306569Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

9
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 07ca76f3-fd12-4112-8210-181f369f483a · inbound

Teaching Models to Express Their Uncertainty in Words cites this paper.

Teaching Models to Express Their Uncertainty in Words Truthful AI: Developing and governing AI that does not lie

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T17:36:08.619241Z

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=2026-05-16T17:36:08.566658Z digest=sha256:519688e74d86a22f690835ffa8a44b4bdfe8f2427a45402d74913054445fdc8e

Observation 35d689ff-737c-4a3a-aa5c-116e460b0e67 · inbound

Language Models (Mostly) Know What They Know cites this paper.

Language Models (Mostly) Know What They Know Truthful AI: Developing and governing AI that does not lie

Reference 196

Resolution
verified exact
arxiv_id, observed 2026-05-10T15:42:47.533040Z

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=arxiv_source observed=2026-05-10T15:42:47.274448Z digest=sha256:86e784e1e0e09827667f8651682a87cc5506fdf62ca3f14823f2d6a80ccdebf6

Observation 12269bc7-6dd8-4ba7-89e7-e45b05c82c0f · inbound

Discovering Latent Knowledge in Language Models Without Supervision cites this paper.

Discovering Latent Knowledge in Language Models Without Supervision Truthful AI: Developing and governing AI that does not lie

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-15T20:34:08.298850Z

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=2026-05-15T20:34:08.207848Z digest=sha256:23fb52c14b0c4237d98d71b15c3af069979c76c83eb006d478c791d27500b298

Observation 7ac089c5-b146-410a-852e-96ae49a86856 · inbound

Transparent NLP: Using RAG and LLM Alignment for Privacy Q&A cites this paper.

Transparent NLP: Using RAG and LLM Alignment for Privacy Q&A Truthful AI: Developing and governing AI that does not lie

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-08T14:50:24.306569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T14:50:24.306569Z digest=sha256:a29a573b4d6b38fb2ff2051065b6de6223c3b20c60edbb9f647fa0b4fe5d0baf

Observation a82fb309-c89b-4e90-b9a9-7c79c4898c7f · inbound

Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs cites this paper.

Utility Engineering: Analyzing and Controlling Emergent Value Systems in AIs Truthful AI: Developing and governing AI that does not lie

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-08T00:04:57.097301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:04:57.097301Z digest=sha256:01b57049521cf99d2c554fc3c5f5c545c058f336fd8e4f488541ba5bbe61cd69

Observation 865f5c98-ff54-4c57-bf5d-8f2520c17bce · inbound

Probing the Geometry of Truth: Consistency and Generalization of Truth Directions in LLMs Across Logical Transformations and Question Answering Tasks cites this paper.

Probing the Geometry of Truth: Consistency and Generalization of Truth Directions in LLMs Across Logical Transformations and Question Answering Tasks Truthful AI: Developing and governing AI that does not lie

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T12:02:52.756243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:02:52.756243Z digest=sha256:ae4ddbbe7ee00639f48bd7a442ca5a64b73151f335d540771b2cedf4490828cf

Observation e963b313-e3ce-4a8f-a981-2ad6bf27bafc · inbound

Out of Control -- Why Alignment Needs Formal Control Theory (and an Alignment Control Stack) cites this paper.

Out of Control -- Why Alignment Needs Formal Control Theory (and an Alignment Control Stack) Truthful AI: Developing and governing AI that does not lie

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T23:26:57.507257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:26:57.507257Z digest=sha256:6623b4b5f7e75f0c1d32b99a37aa59d4aa9b08a4a4e10150c18002323a102d45

Observation c5d2a7b3-76ca-464c-a9f5-587b1fd3ca29 · inbound

A Mathematical Theory of Discursive Networks cites this paper.

A Mathematical Theory of Discursive Networks Truthful AI: Developing and governing AI that does not lie

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T19:08:18.450169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:08:18.450169Z digest=sha256:d15bda697501d1280b796f0a73c10f7e234514dd518fad51f8c20dca2ce55a5f

Observation 7e5cacf8-4d0b-4171-bba9-1749278e2d02 · inbound

Deceive, Detect, and Disclose: Large Language Models Play Mini-Mafia cites this paper.

Deceive, Detect, and Disclose: Large Language Models Play Mini-Mafia Truthful AI: Developing and governing AI that does not lie

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-18T13:26:24.876334Z

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=arxiv_source observed=2026-05-18T13:25:17.313704Z digest=sha256:476f98ea80ad12403d04d283576eb5f48d0d676187c2298186a95af630801ff3

Observation c588f47c-7dec-4a4f-8959-f74ffb077b3a · inbound

DECK: A Consistency x Confidence Taxonomy of LLM Hallucinations cites this paper.

DECK: A Consistency x Confidence Taxonomy of LLM Hallucinations Truthful AI: Developing and governing AI that does not lie

Reference 48

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T22:56:19.747489Z

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=arxiv_source observed=2026-06-28T14:57:12.792031Z digest=sha256:bd221d04e772b9de235eb24f8988aac5f97edf380825c63440e7c1c55d9a68b8