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Paper Citation Record · LEDGER

Preference Tuning For Toxicity Mitigation Generalizes Across Languages

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2406.16235.

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

pith.paper-citation-record.v1
2406.16235 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:58:45.210243Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T17:13:44.896134Z

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 2aceaa5b-c48a-42ff-aa50-781aa199fb5d · inbound

Does Unlearning Truly Unlearn? A Black Box Evaluation of LLM Unlearning Methods cites this paper.

Does Unlearning Truly Unlearn? A Black Box Evaluation of LLM Unlearning Methods Preference Tuning For Toxicity Mitigation Generalizes Across Languages

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-12T17:58:45.210243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T17:58:45.210243Z digest=sha256:ea501a486b73b287194e9044960996845763abc3969ed84bc750c3033e0b9a6f

Observation adb34e46-df8e-40f3-9fda-79761d91fc62 · inbound

Aligning LLMs with Domain Invariant Reward Models cites this paper.

Aligning LLMs with Domain Invariant Reward Models Preference Tuning For Toxicity Mitigation Generalizes Across Languages

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-10T22:45:12.315612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:45:12.315612Z digest=sha256:94d44e78f57e1d8707a7e1fc39a8a464e1c223ec7dbe2f1e749099824457c044

Observation 8520a4dd-f0c0-4174-9a4c-159d9ac6cb45 · inbound

TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching cites this paper.

TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching Preference Tuning For Toxicity Mitigation Generalizes Across Languages

Reference 144

Resolution
verified exact
arxiv_id, observed 2026-05-13T04:57:17.261860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-13T04:55:55.013900Z digest=sha256:e114a8487974d8a337186118d5dd9acc09317cc24a5f2115b16ac483b665a576

Observation fe92344c-7b16-411d-9ef9-c09647064822 · inbound

TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching cites this paper.

TokenRatio: Principled Token-Level Preference Optimization via Ratio Matching Preference Tuning For Toxicity Mitigation Generalizes Across Languages

Reference 144

Resolution
verified exact
arxiv_id, observed 2026-05-15T05:45:06.681330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-15T05:41:10.714594Z digest=sha256:b260b28124e0ebc0c244f6cc6a18b6953f10f3d15c33fb7a3da6c9ceb3226935

Observation d557ac99-f1f9-40ec-8400-b32bcbcf1357 · inbound

Cyberbullying Governance on Social Media: A Unified Framework from Content Identification to Intervention cites this paper.

Cyberbullying Governance on Social Media: A Unified Framework from Content Identification to Intervention Preference Tuning For Toxicity Mitigation Generalizes Across Languages

Reference 221

Resolution
verified exact
arxiv_id, observed 2026-06-29T17:13:44.897501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-06-29T17:05:30.141119Z digest=sha256:249e5a97e291f5ee3d4abc40ec167b989f0a2c8e00ff13f04b0eaf647cd2bd36