Paper Citation Record · LEDGER

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

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 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 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:05:51.100865Z

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 2026-08-15T06:32:42.880941+00:00.

Observation 9229ee25-e6a6-411d-99c5-e9dcfd3705f3 · inbound

Socio-Culturally Aware Evaluation Framework for LLM-Based Content Moderation cites this paper.

Socio-Culturally Aware Evaluation Framework for LLM-Based Content Moderation Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T13:05:51.100865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74d04853-4c35-4c61-9dfc-f0bb511e34f8 · inbound

ICM-Assistant: Instruction-tuning Multimodal Large Language Models for Rule-based Explainable Image Content Moderation cites this paper.

ICM-Assistant: Instruction-tuning Multimodal Large Language Models for Rule-based Explainable Image Content Moderation Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T05:01:12.220786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b442214-fe35-4712-80ef-f6a06e762b45 · inbound

Clear Preferences Leave Traces: Reference Model-Guided Sampling for Preference Learning cites this paper.

Clear Preferences Leave Traces: Reference Model-Guided Sampling for Preference Learning Adapting Large Language Models for Content Moderation: Pitfalls in Data Engineering and Supervised Fine-tuning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T14:39:22.640623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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.

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.

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.

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.

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.