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Paper Citation Record · LEDGER

On Evaluating The Performance of Watermarked Machine-Generated Texts Under Adversarial Attacks

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2407.04794.

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

pith.paper-citation-record.v1
2407.04794 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 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:22:08.290441Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T13:22:08.562983Z

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 c36a2ee2-2b74-4813-84ee-6fe312c4d0c5 · inbound

LLM Encoder vs. Decoder: Robust Detection of Chinese AI-Generated Text with LoRA cites this paper.

LLM Encoder vs. Decoder: Robust Detection of Chinese AI-Generated Text with LoRA On Evaluating The Performance of Watermarked Machine-Generated Texts Under Adversarial Attacks

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-05T13:22:08.580885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-05T13:22:08.290441Z digest=sha256:57c2cf1d97cd86165d4caa98005d81856508c7c23ae7ee6687b8cc555f1b1f78

Observation a9f7d773-9aae-4b4c-a6a9-a8e97877789a · inbound

Character-Level Perturbations Disrupt LLM Watermarks cites this paper.

Character-Level Perturbations Disrupt LLM Watermarks On Evaluating The Performance of Watermarked Machine-Generated Texts Under Adversarial Attacks

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-04T19:46:51.519469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:46:51.519469Z digest=sha256:ec0a6918f9628ad02a4aa8ae921104a2bf2c2bea5385a426ef3b8e055141c7d8