Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2410.08811.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T00:39:02.309959Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T14:59:54.708937Z
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 9b274567-d45c-4fa0-863a-e2c07d94652b · inbound
Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation cites this paper.
Synthetic Poisoning Attacks: The Impact of Poisoned MRI Image on U-Net Brain Tumor Segmentation PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T00:39:02.309959Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 195a3ecc-af48-47ed-b019-3c02b3b79a90 · inbound
Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead cites this paper.
Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning
Reference 88
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:36:29.676305Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fca70983-ea4d-4e35-9b7a-b07eeb09401d · inbound
LLM Hypnosis: Exploiting User Feedback for Unauthorized Knowledge Injection to All Users cites this paper.
LLM Hypnosis: Exploiting User Feedback for Unauthorized Knowledge Injection to All Users PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T06:02:07.810301Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation d13cfdac-bde0-4bf9-b4ea-e227a2d5ba2b · 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 PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning
Reference 94
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T17:46:17.800744Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e1ebc7a2-c75f-4e95-bc1c-acc5bdca919c · inbound
SafeTune: Mitigating Data Poisoning in LLM Fine-Tuning for RTL Code Generation cites this paper.
SafeTune: Mitigating Data Poisoning in LLM Fine-Tuning for RTL Code Generation PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning
Reference 22
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T09:36:26.575265Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 4617f6c5-db4b-46cd-98eb-fca9caaf0729 · inbound
Efficient Preference Poisoning Attack on Offline RLHF cites this paper.
Efficient Preference Poisoning Attack on Offline RLHF PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning
Reference 139
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-09T05:50:27.117761Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 7884badc-28e9-4edd-b089-56613bc33fef · 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 PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning
Reference 14
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-14T21:02:58.867033Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation b4f2d092-324a-4e17-ad18-99c4bc23e4d5 · inbound
Be Kind, Rewrite: Benign Projections via Rewriting Defend Against LLM Data Poisoning Attacks cites this paper.
Be Kind, Rewrite: Benign Projections via Rewriting Defend Against LLM Data Poisoning Attacks PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T08:58:10.448234Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 408b2067-284f-42a6-ab78-1527d5bf42e0 · inbound
AI Integrity: Defending Against Backdoors and Secret Loyalties cites this paper.
AI Integrity: Defending Against Backdoors and Secret Loyalties PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T14:59:54.712176Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.