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Paper Citation Record · LEDGER

Is poisoning a real threat to LLM alignment? Maybe more so than you think

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2406.12091.

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

pith.paper-citation-record.v1
2406.12091 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:24:12.423674Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T17:38:43.793888Z

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 b903ce8e-b760-4d83-8de6-fa1191ea6b6e · 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 Is poisoning a real threat to LLM alignment? Maybe more so than you think

Reference 150

Resolution
unresolved
no resolver link, observed 2026-08-16T11:24:12.423674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:24:12.423674Z digest=sha256:41b65e1efe6090089a688487d3733616d9a8ff61f6a4d0e4077ad60f2e699d7a

Observation dadf7f30-775f-437c-b585-482100867b2e · 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 Is poisoning a real threat to LLM alignment? Maybe more so than you think

Reference 290

Resolution
unresolved
no resolver link, observed 2026-08-06T21:36:47.325427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:36:47.325427Z digest=sha256:ab2d4303164829f0add84055253ced38c1f90e2796f74a944989eb1d8b722938

Observation 4f3ed951-42a0-4b2b-9cb0-6855e1369b1b · 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 Is poisoning a real threat to LLM alignment? Maybe more so than you think

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-19T06:02:07.872783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-19T05:58:17.452837Z digest=sha256:194e23466462686ce3859de116119c6c6f5b24fdc353fdc3277c92fee6b65c48

Observation ca4cc7a9-7d41-48c1-9632-1961ab569f29 · inbound

Teach a Reward Model to Correct Itself: Reward Guided Adversarial Failure Discovery for Robust Reward Modeling cites this paper.

Teach a Reward Model to Correct Itself: Reward Guided Adversarial Failure Discovery for Robust Reward Modeling Is poisoning a real threat to LLM alignment? Maybe more so than you think

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-19T05:17:05.836576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-19T05:16:22.274580Z digest=sha256:93536630c044ac71379291f458661c280fc1fc4af7e8c25c8ee732ce0f6a35a9

Observation f5ca4bfd-43cd-4f6c-9feb-6f33dad7aade · inbound

POLARIS: Explainable Artificial Intelligence for Mitigating Power Side-Channel Leakage cites this paper.

POLARIS: Explainable Artificial Intelligence for Mitigating Power Side-Channel Leakage Is poisoning a real threat to LLM alignment? Maybe more so than you think

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T12:04:44.883293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:04:44.883293Z digest=sha256:e6715f56d1feebba89c27aa42dcacb4929f4815509a0022e0ba6a1b94612862b

Observation f4afd77e-a7ed-43ec-81d3-6185cd27af19 · inbound

Poison Once, Refuse Forever: Weaponizing Alignment for Injecting Bias in LLMs cites this paper.

Poison Once, Refuse Forever: Weaponizing Alignment for Injecting Bias in LLMs Is poisoning a real threat to LLM alignment? Maybe more so than you think

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-15T16:51:54.830133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:51:54.830133Z digest=sha256:d8f4aa216f6b3c52da559f3071fde2d765b759463a1d311f9b12473fdd786f5b

Observation e4a434f6-a13b-46ff-9b5d-d0c8030bacea · inbound

FedDetox: Robust Federated SLM Alignment via On-Device Data Sanitization cites this paper.

FedDetox: Robust Federated SLM Alignment via On-Device Data Sanitization Is poisoning a real threat to LLM alignment? Maybe more so than you think

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:56:01.761956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T17:22:40.613937Z digest=sha256:aaa5ac000da8896e98d4749eaa7eb4654f2d4b02cc4d0770c8aeb2c06822d09b

Observation b3f4eece-ae85-48c8-9bc4-0d7243610676 · inbound

BadDLM: Backdooring Diffusion Language Models with Diverse Targets cites this paper.

BadDLM: Backdooring Diffusion Language Models with Diverse Targets Is poisoning a real threat to LLM alignment? Maybe more so than you think

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:11:25.980424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-12T04:30:13.417357Z digest=sha256:9b06f2ca2612e5896ee4f349779746b33c6c4a1e52aa9de019ca60987c31ea06

Observation 5c183eb1-f2cd-45fa-a4e9-70a488b8f45a · inbound

Loss Landscape Poisoning: Targeted Extraction of Unseen Training Data from LLMs cites this paper.

Loss Landscape Poisoning: Targeted Extraction of Unseen Training Data from LLMs Is poisoning a real threat to LLM alignment? Maybe more so than you think

Reference 61

Resolution
verified exact
arxiv_id, observed 2026-07-03T17:38:43.795430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-27T03:59:30.468854Z digest=sha256:69bd7881efb33ca8af92cf24c8c080d75cdd5a31980e6a99f6fc0ec91edd93fe