Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Waterfall: Framework for Robust and Scalable Text Watermarking and Provenance for LLMs
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2407.04411.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T22:49:58.584755Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T05:00:57.256115Z
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 1dae55d9-880f-4e53-9a28-23b9c51a5205 · inbound
Robust Multi-bit Text Watermark with LLM-based Paraphrasers cites this paper.
Robust Multi-bit Text Watermark with LLM-based Paraphrasers Waterfall: Framework for Robust and Scalable Text Watermarking and Provenance for LLMs
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T22:49:58.584755Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b95bd14d-b86e-406c-a78c-c2c31246a605 · inbound
Paladin: Defending LLM-enabled Phishing Emails with a New Trigger-Tag Paradigm cites this paper.
Paladin: Defending LLM-enabled Phishing Emails with a New Trigger-Tag Paradigm Waterfall: Framework for Robust and Scalable Text Watermarking and Provenance for LLMs
Reference 156
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T22:33:34.172710Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f81a5b0b-7a8c-4a2e-bf48-512b74991ef5 · inbound
When Only the Final Text Survives: Implicit Execution Tracing for Multi-Agent Auditing cites this paper.
When Only the Final Text Survives: Implicit Execution Tracing for Multi-Agent Auditing Waterfall: Framework for Robust and Scalable Text Watermarking and Provenance for LLMs
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T05:52:05.468550Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f7797c44-d2e6-44e5-90ee-1d6a065cf43f · inbound
Dataset Watermarking for Closed LLMs with Provable Detection cites this paper.
Dataset Watermarking for Closed LLMs with Provable Detection Waterfall: Framework for Robust and Scalable Text Watermarking and Provenance for LLMs
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T05:00:57.261229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation f5634625-0c6f-4d12-9f95-d43a80ee1172 · inbound
Can Watermarking Techniques Help Prevent LLM Model Stealing? cites this paper.
Can Watermarking Techniques Help Prevent LLM Model Stealing? Waterfall: Framework for Robust and Scalable Text Watermarking and Provenance for LLMs
Reference 68
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T09:13:20.561611Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.