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Paper Citation Record · LEDGER

TextGuard: Provable Defense against Backdoor Attacks on Text Classification

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2311.11225.

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

pith.paper-citation-record.v1
2311.11225 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:43:24.734540Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T23:28:40.684095Z

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 b2d64ae5-bd58-4378-aa97-f3fab945aa9c · inbound

Certifying Language Model Robustness with Fuzzed Randomized Smoothing: An Efficient Defense Against Backdoor Attacks cites this paper.

Certifying Language Model Robustness with Fuzzed Randomized Smoothing: An Efficient Defense Against Backdoor Attacks TextGuard: Provable Defense against Backdoor Attacks on Text Classification

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-08T17:43:24.734540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:43:24.734540Z digest=sha256:d778453979bb5b9768392305b6f63e210f924143fac9ed6671282bff112f7aee

Observation 8e8f6231-f40d-4abc-9b47-c867ca34a124 · inbound

SCOUT: A Defense Against Data Poisoning Attacks in Fine-Tuned Language Models cites this paper.

SCOUT: A Defense Against Data Poisoning Attacks in Fine-Tuned Language Models TextGuard: Provable Defense against Backdoor Attacks on Text Classification

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-16T23:28:40.686743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T23:26:48.405593Z digest=sha256:f938747315d4de4cb0fb6ed1ff4b144e2783aa36a65dcb6dd477fe50c568166c