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Paper Citation Record · LEDGER

Concealed Data Poisoning Attacks on NLP Models

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2010.12563.

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

pith.paper-citation-record.v1
2010.12563 v2

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 2026-08-03T06:30:56.289259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T10:16:38.248004Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:50:11.208012Z

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 0c8be5a4-0139-462a-95bb-a8e3025f9afb · inbound

RapidUn: Influence-Driven Parameter Reweighting for Efficient Large Language Model Unlearning cites this paper.

RapidUn: Influence-Driven Parameter Reweighting for Efficient Large Language Model Unlearning Concealed Data Poisoning Attacks on NLP Models

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-21T17:34:17.377307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-05-21T17:33:06.959574Z digest=sha256:cba2fa2c9aaf637165c61d21d255cf74379a8a6ff48d7cdad6904aa05386e44e

Observation 8f499758-16ba-4934-ae5f-d694e449d34a · inbound

A Red Teaming Framework for Large Language Models: A Case Study on Faithfulness Evaluation cites this paper.

A Red Teaming Framework for Large Language Models: A Case Study on Faithfulness Evaluation Concealed Data Poisoning Attacks on NLP Models

Reference 31

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T19:50:11.209459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.

source=pdf_text observed=2026-06-25T20:58:53.119386Z digest=sha256:0e1491e3507e00b7e7c530248f7a8c9a9e9c4f649eea9fcf8ddb590720687d6f

Observation 94e3bf5e-1d55-4c90-9ca9-e505211f1e21 · inbound

A Red Teaming Framework for Large Language Models: A Case Study on Faithfulness Evaluation cites this paper.

A Red Teaming Framework for Large Language Models: A Case Study on Faithfulness Evaluation Concealed Data Poisoning Attacks on NLP Models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-02T10:16:38.248004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T10:16:38.248004Z digest=sha256:99394950f2b3388c97078aee4303c5b5e6d6a2fac86d0754b5e50b8e69b58ce7

Observation e269dfcf-dbbd-42b0-b2e5-223ba479aa7c · inbound

Pretraining Data Can Be Poisoned through Computational Propaganda cites this paper.

Pretraining Data Can Be Poisoned through Computational Propaganda Concealed Data Poisoning Attacks on NLP Models

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-01T23:44:46.193089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T23:44:46.193089Z digest=sha256:b00df67facaa0df3cfd47de97ba90d80ad3d6f5f09a245e051b5cb491b82d269