Paper Citation Record · LEDGER

Trust & Safety of LLMs and LLMs in Trust & Safety

As of 22 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 2 inbound Pith citation observations for arXiv:2412.02113.

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

pith.paper-citation-record.v1
2412.02113 v2

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:52:33.211135Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:24:20.404079Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T20:36:50.283329Z

Reference resolution

15 of 15 outbound references displayed

verified exact2
verified fuzzy3
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ba573234-8e47-418c-98c7-6166b5d8bd75 · outbound

This paper cites Efficient Diffusion Training via Min-SNR Weighting Strategy.

Trust & Safety of LLMs and LLMs in Trust & Safety Efficient Diffusion Training via Min-SNR Weighting Strategy

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T23:52:33.138118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e113707-49f2-46c2-b386-a9ab9779bd29 · outbound

This paper cites Poisoning web-scale training datasets is practical.

Trust & Safety of LLMs and LLMs in Trust & Safety Poisoning web-scale training datasets is practical

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:52:33.470844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cdabbf06-9c3e-41e6-a560-21aee0fd7a52 · outbound

This paper cites Can Large Language Models Beat Wall Street? Unveiling the Potential of AI in Stock Selection.

Trust & Safety of LLMs and LLMs in Trust & Safety Can Large Language Models Beat Wall Street? Unveiling the Potential of AI in Stock Selection

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T23:52:33.165242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c2049ba-af7c-4d84-800b-8a6b872b8be7 · outbound

This paper cites an unresolved cited work.

Trust & Safety of LLMs and LLMs in Trust & Safety Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-11T23:52:33.455033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 86109da7-6e2c-4af1-939a-bade02a77286 · outbound

This paper cites TruthfulQA: Measuring How Models Mimic Human Falsehoods.

Trust & Safety of LLMs and LLMs in Trust & Safety TruthfulQA: Measuring How Models Mimic Human Falsehoods

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T23:52:33.175030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation deabdaa9-b80d-4677-aa9e-de5d3bb38410 · outbound

This paper cites Red Teaming Language Models with Language Models.

Trust & Safety of LLMs and LLMs in Trust & Safety Red Teaming Language Models with Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T23:52:33.180264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 769bed58-f667-4a87-a90c-622699fbb9c7 · outbound

This paper cites Ignore Previous Prompt: Attack Techniques For Language Models.

Trust & Safety of LLMs and LLMs in Trust & Safety Ignore Previous Prompt: Attack Techniques For Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T23:52:33.185443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39b02c47-3989-475d-9485-0815e79b50b9 · outbound

This paper cites an unresolved cited work.

Trust & Safety of LLMs and LLMs in Trust & Safety Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-11T23:52:33.439409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 274c80ff-c9c9-4848-bde5-c6b46085c4d8 · outbound

This paper cites [TSAM23] Kushal Tirumala, Daniel Simig, Armen Aghajanyan, and Ari S.

Trust & Safety of LLMs and LLMs in Trust & Safety [TSAM23] Kushal Tirumala, Daniel Simig, Armen Aghajanyan, and Ari S

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:52:33.423277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d165d45c-be3a-424c-b648-9730290f3bb8 · outbound

This paper cites Enhanced Meta Label Correction for Coping with Label Corruption.

Trust & Safety of LLMs and LLMs in Trust & Safety Enhanced Meta Label Correction for Coping with Label Corruption

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-11T23:52:33.278700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 014be12d-04a9-406c-bd9d-3bf5d1cc6601 · outbound

This paper cites Evaluating Deduplication Techniques for Economic Research Paper Titles with a Focus on Semantic Similarity using NLP and LLMs.

Trust & Safety of LLMs and LLMs in Trust & Safety Evaluating Deduplication Techniques for Economic Research Paper Titles with a Focus on Semantic Similarity using NLP and LLMs

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-11T23:52:33.255570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d5b66794-1c9a-4478-a818-874cdb0ab865 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Trust & Safety of LLMs and LLMs in Trust & Safety On the Opportunities and Risks of Foundation Models

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-11T23:52:33.148942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4cf405d-df75-4cd1-8afa-69b9d755b911 · outbound

This paper cites On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency, pages 610–623,.

Trust & Safety of LLMs and LLMs in Trust & Safety On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency, pages 610–623,

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:52:33.486594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e37d055d-91eb-41eb-967c-83c4a0bf7aa9 · outbound

This paper cites Extracting Training Data from Large Language Models.

Trust & Safety of LLMs and LLMs in Trust & Safety Extracting Training Data from Large Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-11T23:52:33.159458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f42972ff-40e0-4856-9609-dff798aca032 · outbound

This paper cites TrustLLM: Trustworthiness in Large Language Models.

Trust & Safety of LLMs and LLMs in Trust & Safety TrustLLM: Trustworthiness in Large Language Models

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-11T23:52:33.190758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 518b9297-43a4-4c87-b74c-364bdd806697 · inbound

Red Teaming for Generative AI, Report on a Copyright-Focused Exercise Completed in an Academic Medical Center cites this paper.

Red Teaming for Generative AI, Report on a Copyright-Focused Exercise Completed in an Academic Medical Center Trust & Safety of LLMs and LLMs in Trust & Safety

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T22:24:20.404079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9cdce9d6-999c-4b25-93a6-edbcef3f7362 · inbound

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments cites this paper.

CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments Trust & Safety of LLMs and LLMs in Trust & Safety

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-18T20:36:50.285951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.