Paper Citation Record · LEDGER

Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models

As of 19 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2210.09545.

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

pith.paper-citation-record.v1
2210.09545 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-19T06:30:13.599613+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T07:47:18.350953Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T08:04:28.747447Z

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 f769a2be-802e-49d2-a148-cb62a1571138 · 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 Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models

Reference 74

Resolution: metadata mismatch; arxiv_id, observed 2026-05-15T06:25:21.156152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-19T06:30:13.599613+00:00.

Observation 62a5fc8b-95a8-434c-a918-a514f3b50bbe · inbound

Uncovering and Aligning Anomalous Attention Heads to Defend Against NLP Backdoor Attacks cites this paper.

Uncovering and Aligning Anomalous Attention Heads to Defend Against NLP Backdoor Attacks Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-17T22:02:08.627638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-19T06:30:13.599613+00:00.

Observation 26e22186-fe39-4dba-b99b-97c81c1c6e82 · inbound

BackFlush: Knowledge-Free Backdoor Detection and Elimination with Watermark Preservation in Large Language Models cites this paper.

BackFlush: Knowledge-Free Backdoor Detection and Elimination with Watermark Preservation in Large Language Models Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T21:02:58.931015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-19T06:30:13.599613+00:00.

Observation 80a1cb2f-a269-4774-828b-dbbc367d7bb9 · inbound

Breaking the Rounding Trap: Securing LLMs against Quantization-Conditioned Backdoors cites this paper.

Breaking the Rounding Trap: Securing LLMs against Quantization-Conditioned Backdoors Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-06-30T08:04:28.749090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-19T06:30:13.599613+00:00.