Paper Citation Record · LEDGER

Measure and Improve Robustness in NLP Models: A Survey

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2112.08313.

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

pith.paper-citation-record.v1
2112.08313 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:41:57.177499Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T19:03:06.140956Z

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 f4403971-f577-4d48-a613-714d07dba1c5 · inbound

ART: Automatic multi-step reasoning and tool-use for large language models cites this paper.

ART: Automatic multi-step reasoning and tool-use for large language models Measure and Improve Robustness in NLP Models: A Survey

Reference 114

Resolution: verified exact; arxiv_id, observed 2026-05-16T19:03:06.143565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b4b6511e-8a18-4640-9bcc-7e362750855a · inbound

Towards Action Hijacking of Large Language Model-based Agent cites this paper.

Towards Action Hijacking of Large Language Model-based Agent Measure and Improve Robustness in NLP Models: A Survey

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T15:41:57.177499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2800bca-5293-40f3-a564-438c7123ced4 · inbound

Coordinated Robustness Evaluation Framework for Vision-Language Models cites this paper.

Coordinated Robustness Evaluation Framework for Vision-Language Models Measure and Improve Robustness in NLP Models: A Survey

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T10:40:49.559495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb2b34b4-93ec-4f2f-a0d9-794eab938169 · inbound

Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directions cites this paper.

Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directions Measure and Improve Robustness in NLP Models: A Survey

Reference 183

Resolution: unresolved; no resolver link, observed 2026-08-07T05:42:31.480354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1cb8a16a-f53d-4ec4-a292-e1f16cad1556 · inbound

Evaluation of Adversarial Robustness in Arabic Language Models cites this paper.

Evaluation of Adversarial Robustness in Arabic Language Models Measure and Improve Robustness in NLP Models: A Survey

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T01:26:14.374642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.