Paper Citation Record · LEDGER

The Dark Side of Human Feedback: Poisoning Large Language Models via User Inputs

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2409.00787.

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

pith.paper-citation-record.v1
2409.00787 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:24:12.437463Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T20:58:25.999803Z

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 8c6407ae-54a0-490c-baf0-06e55c8bfbe4 · inbound

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey cites this paper.

Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey The Dark Side of Human Feedback: Poisoning Large Language Models via User Inputs

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:58:26.002895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b7b7ee9d-0863-46f7-b8c2-5f7c0921e9bf · inbound

A Survey on Backdoor Threats in Large Language Models (LLMs): Attacks, Defenses, and Evaluations cites this paper.

A Survey on Backdoor Threats in Large Language Models (LLMs): Attacks, Defenses, and Evaluations The Dark Side of Human Feedback: Poisoning Large Language Models via User Inputs

Reference 120

Resolution: unresolved; no resolver link, observed 2026-08-09T00:50:00.444043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5d35503-d951-48f0-a107-dc721bc91bf3 · inbound

A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment cites this paper.

A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment The Dark Side of Human Feedback: Poisoning Large Language Models via User Inputs

Reference 154

Resolution: unresolved; no resolver link, observed 2026-08-16T11:24:12.437463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 485469a0-bdc5-4ccf-80e5-84675f2a08ea · 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 The Dark Side of Human Feedback: Poisoning Large Language Models via User Inputs

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-05T23:13:02.685636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9b119b3-5e41-43f8-bfac-d349d3739aef · inbound

LLM in the Middle: A Systematic Review of Threats and Mitigations to Real-World LLM-based Systems cites this paper.

LLM in the Middle: A Systematic Review of Threats and Mitigations to Real-World LLM-based Systems The Dark Side of Human Feedback: Poisoning Large Language Models via User Inputs

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-04T17:46:14.370271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a58fb64-3080-4b1b-b706-afef034d9e26 · inbound

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation cites this paper.

Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation The Dark Side of Human Feedback: Poisoning Large Language Models via User Inputs

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T00:29:58.203660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.