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Paper Citation Record · LEDGER

A Holistic Approach to Undesired Content Detection in the Real World

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 22 inbound Pith citation observations for arXiv:2208.03274.

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

pith.paper-citation-record.v1
2208.03274 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 22 of 22 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:39:10.940635Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T13:06:58.683371Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2bba94ca-935b-4b55-abb2-43ad148bad9f · inbound

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

Ignore Previous Prompt: Attack Techniques For Language Models A Holistic Approach to Undesired Content Detection in the Real World

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-11T13:59:31.495804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-11T13:59:31.213830Z digest=sha256:bb12bb843313667ff0844db4a1ed4357c401353abdde9918f0c51d217cd79390

Observation 7571bf72-6d0d-4cc0-8123-3656d96f888e · inbound

Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models cites this paper.

Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models A Holistic Approach to Undesired Content Detection in the Real World

Reference 128

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T06:38:36.858913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-18T06:38:36.517935Z digest=sha256:3ce5a72092865381143c7ef67795444022aa53ff80d9a5ecf1203278555bb078

Observation 1886cb5b-bbb3-4ce1-a883-6104a1a195a2 · inbound

Behind Closed Words: Creating and Investigating the forePLay Annotated Dataset for Polish Erotic Discourse cites this paper.

Behind Closed Words: Creating and Investigating the forePLay Annotated Dataset for Polish Erotic Discourse A Holistic Approach to Undesired Content Detection in the Real World

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-11T05:31:08.376993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:31:08.376993Z digest=sha256:324fc66edee359719a4887e070874f01757d702c1d57ac9a16ebb9500c6d0c08

Observation 960f04e7-23dc-40a5-a58c-f7c9b137883a · inbound

Digital Guardians: Can GPT-4, Perspective API, and Moderation API reliably detect hate speech in reader comments of German online newspapers? cites this paper.

Digital Guardians: Can GPT-4, Perspective API, and Moderation API reliably detect hate speech in reader comments of German online newspapers? A Holistic Approach to Undesired Content Detection in the Real World

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-10T22:38:11.620427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:38:11.620427Z digest=sha256:c9decdb5086086cebb8982de57cc94bc56edccd57de40f98e798985eaa0a2863

Observation ec8c0ee7-6f7b-439f-92fe-9416b5610e09 · inbound

aiXamine: Simplified LLM Safety and Security cites this paper.

aiXamine: Simplified LLM Safety and Security A Holistic Approach to Undesired Content Detection in the Real World

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-16T11:39:10.940635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:39:10.940635Z digest=sha256:074f0da2e428095a74702d6616ef545ec1cbeaa4245e63b2f57732c3a962d111

Observation ae1d27e0-db97-4e4c-9366-00dfdd06fcfe · inbound

Understanding and Mitigating Risks of Generative AI in Financial Services cites this paper.

Understanding and Mitigating Risks of Generative AI in Financial Services A Holistic Approach to Undesired Content Detection in the Real World

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-16T10:19:10.496545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:19:10.496545Z digest=sha256:4893a94785595a34f24a0ceed4827624a7fd2d67b2862aa51d6a79d99831552c

Observation 29458343-41f4-45c8-b131-c17de6ef1711 · inbound

A Large-Scale Empirical Analysis of Custom GPTs' Vulnerabilities in the OpenAI Ecosystem cites this paper.

A Large-Scale Empirical Analysis of Custom GPTs' Vulnerabilities in the OpenAI Ecosystem A Holistic Approach to Undesired Content Detection in the Real World

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T22:06:44.288329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:06:44.288329Z digest=sha256:2df6d652cd04b703ae2d78b5c1342530b86f4901dedda8457f4013d6cb94e7e9

Observation fc3b47ae-d489-4c17-a7db-e115376c280c · inbound

ReGA: Model-Based Safeguard for LLMs via Representation-Guided Abstraction cites this paper.

ReGA: Model-Based Safeguard for LLMs via Representation-Guided Abstraction A Holistic Approach to Undesired Content Detection in the Real World

Reference 87

Resolution
verified exact
arxiv_id, observed 2026-05-19T11:37:15.936802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-19T11:34:09.428653Z digest=sha256:1b95e0a068fab5fd614a4122660ebe65715f12645d48067ebd0cc6cc28d40783

Observation 95f93033-9560-45a8-bcae-3076a86fa639 · inbound

SEALGuard: Safeguarding the Multilingual Conversations in Southeast Asian Languages for LLM Software Systems cites this paper.

SEALGuard: Safeguarding the Multilingual Conversations in Southeast Asian Languages for LLM Software Systems A Holistic Approach to Undesired Content Detection in the Real World

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T18:28:43.934564Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:28:43.934564Z digest=sha256:b79514c20ecab900b93a0e6a5c2d3b9568d4fe6b779319472d712d9427a8584a

Observation 17a36167-b357-4480-bee9-490901646137 · inbound

Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT cites this paper.

Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT A Holistic Approach to Undesired Content Detection in the Real World

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-04T14:50:30.992141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T14:50:30.992141Z digest=sha256:a94abaf89eebf74590e64c86ec534588283eabc403b40f873050a45e7f0a8b0d

Observation 35db1525-7155-47e0-9ca4-3ac1bf0c7fa9 · inbound

GuardReasoner-Omni: A Reasoning-based Multi-modal Guardrail for Text, Image, Video, and Audio cites this paper.

GuardReasoner-Omni: A Reasoning-based Multi-modal Guardrail for Text, Image, Video, and Audio A Holistic Approach to Undesired Content Detection in the Real World

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-03T05:07:09.386730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:07:09.386730Z digest=sha256:888567bdcaed499ad358484a69afa9d8632908f14bf16c6a00c8ce3e9cddebae

Observation dc21f6c3-6724-43c2-8c5f-32cef1d4e304 · inbound

Response-Based Knowledge Distillation for Multilingual Jailbreak Prevention Unwittingly Compromises Safety cites this paper.

Response-Based Knowledge Distillation for Multilingual Jailbreak Prevention Unwittingly Compromises Safety A Holistic Approach to Undesired Content Detection in the Real World

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-17T01:28:48.799684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-17T01:27:16.967080Z digest=sha256:e50c6208925221a59342c6e985ee40020be7a3a5d335df60ac6eb043cdfd95ad

Observation 98b44a5c-3ee8-4942-9058-04915b276034 · inbound

Predict, Don't React: Value-Based Safety Forecasting for LLM Streaming cites this paper.

Predict, Don't React: Value-Based Safety Forecasting for LLM Streaming A Holistic Approach to Undesired Content Detection in the Real World

Reference 12

Resolution
unresolved
no resolver link, observed 2026-07-13T11:43:31.089245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T11:43:31.089245Z digest=sha256:79d9d79f7d5b681382d59dcb735506c3c3e8bc726a5d14f4293663283eaf4987

Observation 945b456b-7538-433d-b7c0-7265147d2d27 · inbound

VoxSafeBench: Not Just What Is Said, but Who, How, and Where cites this paper.

VoxSafeBench: Not Just What Is Said, but Who, How, and Where A Holistic Approach to Undesired Content Detection in the Real World

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-10T10:24:22.129507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-10T10:19:28.041282Z digest=sha256:3e9ccb6ee2e44f9a845b3830065f126aee99fa6cac081ca46ddb3ede119ce1ec

Observation d36ec0b3-12a0-4029-a2a9-def6c38c666e · inbound

Test-Time Safety Alignment cites this paper.

Test-Time Safety Alignment A Holistic Approach to Undesired Content Detection in the Real World

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:51:43.314183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-07T16:06:37.244288Z digest=sha256:b96c8be400caf354e1f3ccbff1c63bdfc7860607a715d4a7e95e47d60fe90245

Observation b8c0d322-4c2c-4b4a-9de7-719b014adb7b · inbound

AI Content Moderation in Therapy Conversations cites this paper.

AI Content Moderation in Therapy Conversations A Holistic Approach to Undesired Content Detection in the Real World

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-06-29T21:03:58.416947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-29T21:02:26.865075Z digest=sha256:25f7d894c4fa893b116c7af5018320b8747959c449a84dc08b78c6f19a3993e6

Observation 05c10576-7de2-48e1-9a74-96b54911bc59 · inbound

$D^2$-Monitor: Dynamic Safety Monitoring for Diffusion LLMs via Hesitation-Aware Routing cites this paper.

$D^2$-Monitor: Dynamic Safety Monitoring for Diffusion LLMs via Hesitation-Aware Routing A Holistic Approach to Undesired Content Detection in the Real World

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-06-29T22:03:59.808267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-29T22:03:25.762772Z digest=sha256:7db81104fb6042003b072a253164a92a4303f53d6382e62115597bebc3cd51c8

Observation 95c790ca-7fc2-4ab8-9e9c-0e341194407e · inbound

Learning from Mistakes: Can LLM Self-Recover after Misalignment? cites this paper.

Learning from Mistakes: Can LLM Self-Recover after Misalignment? A Holistic Approach to Undesired Content Detection in the Real World

Reference 22

Resolution
unresolved
no resolver link, observed 2026-07-13T18:51:10.298187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T18:51:10.298187Z digest=sha256:397f2b3dd5aa8eed867092ce1342f01433c3a7f8012f938d393454a725d278d6

Observation a5eec1c6-b462-4521-b7db-96e4f953b050 · inbound

Yuvion LLM: An Adversarially-Aware Large Language Model for Content And AI Safety cites this paper.

Yuvion LLM: An Adversarially-Aware Large Language Model for Content And AI Safety A Holistic Approach to Undesired Content Detection in the Real World

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-06-29T00:52:55.802055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-29T00:46:03.210076Z digest=sha256:e8f29bb1d25cf96c5ae62076347f4e8470437451117e029229e3f643e855d9f3

Observation 4a973d41-9d02-47d2-a9bf-a133257b3289 · inbound

Robust Harmful Features Under Jailbreak Attacks: Mechanistic Evidence from Attention Head Specialization in Large Language Models cites this paper.

Robust Harmful Features Under Jailbreak Attacks: Mechanistic Evidence from Attention Head Specialization in Large Language Models A Holistic Approach to Undesired Content Detection in the Real World

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-07-01T17:35:51.371484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-29T03:35:34.594617Z digest=sha256:108a42c3bc711b830609d36005814c02b449631817e83407b67ca5b3c1678e88

Observation 425d607f-c7d4-44b5-9195-0eaf66fa9f7d · inbound

AI Native Games: A Survey and Roadmap cites this paper.

AI Native Games: A Survey and Roadmap A Holistic Approach to Undesired Content Detection in the Real World

Reference 91

Resolution
verified exact
arxiv_id, observed 2026-07-02T13:06:58.684741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-02T12:59:20.908659Z digest=sha256:b9113b5237d493457b4e62c2ec414e7a9eeec5aba5b9ca33dd32134111c97fc0

Observation f3d89b71-7b73-46ad-abc0-ce6be5bdc526 · inbound

AI Native Games: A Survey and Roadmap cites this paper.

AI Native Games: A Survey and Roadmap A Holistic Approach to Undesired Content Detection in the Real World

Reference 89

Resolution
unresolved
no resolver link, observed 2026-07-12T09:30:07.729486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T09:30:07.729486Z digest=sha256:3abf1fac89a611868bac4867de357aeb72c899f6fdfb6cf4a8f05a94cc79d350