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Paper Citation Record · LEDGER

Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2310.03400.

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

pith.paper-citation-record.v1
2310.03400 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T10:23:06.180903Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T23:03:34.350605Z

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 2a37c782-80cc-47ee-bcf4-6ce02507cca2 · inbound

Seeing Like an AI: How LLMs Apply (and Misapply) Wikipedia Neutrality Norms cites this paper.

Seeing Like an AI: How LLMs Apply (and Misapply) Wikipedia Neutrality Norms Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-23T23:03:34.353964Z

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=2026-05-23T23:03:17.165358Z digest=sha256:6df033e462884713c5e902a24c27712b70dee622b82bd9193ba068c3f23ef554

Observation 820bd457-a9fc-43ce-86e0-b4426eae7a3f · inbound

Bridging the Safety Gap: A Guardrail Pipeline for Trustworthy LLM Inferences cites this paper.

Bridging the Safety Gap: A Guardrail Pipeline for Trustworthy LLM Inferences Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-08T10:23:06.180903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:23:06.180903Z digest=sha256:157fd0d7004a8549560cf5d44fcef635663284bd1f6207ce854f452fd474ee16

Observation e6ada4a3-ff70-4541-805a-16b548cf52d8 · inbound

ChineseHarm-Bench: A Chinese Harmful Content Detection Benchmark cites this paper.

ChineseHarm-Bench: A Chinese Harmful Content Detection Benchmark Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T04:19:31.560339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:19:31.560339Z digest=sha256:d1043fa372fce51e2e78b320e278d9fc66bf4c46f1ee1d9a6c64c594bd296a91

Observation 13f37c57-1bf9-4e76-ac14-1058c0bd62dd · inbound

Embedding-based Retrieval in Multimodal Content Moderation cites this paper.

Embedding-based Retrieval in Multimodal Content Moderation Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T21:26:05.894226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:26:05.894226Z digest=sha256:4b026f0b1fc872f36d8afa9913decfeb4d9402e668b36f58b07362818bec9e77

Observation a840b9eb-24f8-4211-8586-07bbbfc2e860 · inbound

Lost in Pronunciation: Detecting Chinese Offensive Language Disguised by Phonetic Cloaking Replacement cites this paper.

Lost in Pronunciation: Detecting Chinese Offensive Language Disguised by Phonetic Cloaking Replacement Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T18:40:24.374688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:40:24.374688Z digest=sha256:c69037d0671e86c0b050f351f86c100c820538a7096f8bb99057cefdd0a5704c

Observation 71de29d7-7c0f-430c-8a2d-0990e53459ca · inbound

Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation cites this paper.

Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T14:58:43.165069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:58:43.165069Z digest=sha256:9b00a26d46e36d663a2e725c8601ba83d707185278a44147814d8aa16cd85712

Observation 82aeb85b-6201-4f3e-bbd0-c5812320939c · inbound

Guardians and Offenders: A Survey on Harmful Content Generation and Safety Mitigation of LLM cites this paper.

Guardians and Offenders: A Survey on Harmful Content Generation and Safety Mitigation of LLM Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning

Reference 160

Resolution
unresolved
no resolver link, observed 2026-08-05T23:13:04.995782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T23:13:04.995782Z digest=sha256:5d4f26244c671796e5ee8be45f61cb630de99f2d18ce3f0fb154200234d5b9ce