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Paper Citation Record · LEDGER

Challenges in Detoxifying Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2109.07445.

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

pith.paper-citation-record.v1
2109.07445 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 2026-08-09T06:31:02.800959+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:26:05.971383Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T13:33:28.439743Z

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 bc9dd14a-fc78-4273-92cd-32bd42afb392 · inbound

A General Language Assistant as a Laboratory for Alignment cites this paper.

A General Language Assistant as a Laboratory for Alignment Challenges in Detoxifying Language Models

Reference 252

Resolution
verified exact
arxiv_id, observed 2026-05-11T14:22:59.343502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-11T14:22:57.925354Z digest=sha256:3193419aec25840aa1d60a2eeb9054cca338c2962269a592dfbe8c3923944be5

Observation 92ed9766-bda1-4a38-9148-66d1467b19b2 · inbound

Ethical and social risks of harm from Language Models cites this paper.

Ethical and social risks of harm from Language Models Challenges in Detoxifying Language Models

Reference 290

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:24:30.322596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-11T18:24:28.835688Z digest=sha256:e65e24f494e9fa294ce5608a4775c6d9aa9f11abeb72c934b74567015d16fca4

Observation 186a5027-f14d-4885-85f4-8e785660a588 · inbound

Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model cites this paper.

Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model Challenges in Detoxifying Language Models

Reference 72

Resolution
verified exact
arxiv_id, observed 2026-05-24T12:14:26.647929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-24T12:10:49.690618Z digest=sha256:32f840f0af6b9b9e5abb11a2d4f306d7c9a3a9d7f9acc9350bd78f5ba3f047f5

Observation ee1b8db8-7624-4e50-87db-a35cc5a4277a · inbound

GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts cites this paper.

GPTFUZZER: Red Teaming Large Language Models with Auto-Generated Jailbreak Prompts Challenges in Detoxifying Language Models

Reference 67

Resolution
verified exact
arxiv_id, observed 2026-05-15T06:25:21.123453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T06:25:20.966510Z digest=sha256:305fc2c21911a57b1e068f0eec467beca72877aeddd5d6adf626b677e647b85d

Observation fa4c0692-db09-4855-b1fc-85ec18622ced · inbound

TrustLLM: Trustworthiness in Large Language Models cites this paper.

TrustLLM: Trustworthiness in Large Language Models Challenges in Detoxifying Language Models

Reference 246

Resolution
verified exact
arxiv_id, observed 2026-05-18T11:17:08.696987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T11:17:08.108565Z digest=sha256:45d71cc2f9c6e9ccf85b6a15ec00644796111035d4c45a44d6703a9e6fce33b9

Observation 76698800-6522-4e0e-aaad-01e1f260eb78 · inbound

Moderating Harm: Benchmarking Large Language Models for Cyberbullying Detection in YouTube Comments cites this paper.

Moderating Harm: Benchmarking Large Language Models for Cyberbullying Detection in YouTube Comments Challenges in Detoxifying Language Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T14:26:05.971383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:26:05.971383Z digest=sha256:b0a789e4853fbcaf267ddb49de8960a82d5eb39f2f2684a59d4383be89a30b51

Observation d6f11497-6607-47b9-81c4-bce4f86b16c5 · inbound

When Large Language Models Meet Law: Dual-Lens Taxonomy, Technical Advances, and Ethical Governance cites this paper.

When Large Language Models Meet Law: Dual-Lens Taxonomy, Technical Advances, and Ethical Governance Challenges in Detoxifying Language Models

Reference 194

Resolution
unresolved
no resolver link, observed 2026-08-06T18:37:11.264262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:37:11.264262Z digest=sha256:c3fe0deb99426f490e58be438ea5cc4e323ccf9afc739c0b22629e360bf68972

Observation eabeb2e8-80d5-4dc2-b9c7-1693c012adc9 · inbound

Model Misalignment and Language Change: Traces of AI-Associated Language in Unscripted Spoken English cites this paper.

Model Misalignment and Language Change: Traces of AI-Associated Language in Unscripted Spoken English Challenges in Detoxifying Language Models

Reference 96

Resolution
unresolved
no resolver link, observed 2026-08-06T10:23:58.094942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T10:23:58.094942Z digest=sha256:1805730a09947091567aa2a4da52bdeb5ca5e8471dda6f38a8a88e6d6a88e86e

Observation 3e9ac3c4-409c-4884-a32f-97a52c9211df · inbound

Ethics Testing: Proactive Identification of Generative AI System Harms cites this paper.

Ethics Testing: Proactive Identification of Generative AI System Harms Challenges in Detoxifying Language Models

Reference 73

Resolution
verified exact
arxiv_id, observed 2026-05-11T14:56:08.093038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-09T20:49:22.147548Z digest=sha256:da62ad73f500184c736e7acd84fafad39dc776eaaf647a2ccee82fdc0a348077

Observation 12ba0c4b-f95f-4d5a-8c36-19e1d2ec3a9b · inbound

Where Does Toxicity Live? Mechanistic Localization and Targeted Suppression in Language Models cites this paper.

Where Does Toxicity Live? Mechanistic Localization and Targeted Suppression in Language Models Challenges in Detoxifying Language Models

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-06-29T13:33:28.441271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-29T13:25:40.986336Z digest=sha256:f1d3d5e26b89b83f81e31ba15f38e290b95082145073ab8275bebd3756adf124