Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Unifying Human and Statistical Evaluation for Natural Language Generation
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1904.02792.
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 2026-08-11T22:57:01.677969Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T19:51:09.822886Z
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 8262b2bc-3063-465d-9c2e-a697dd650092 · inbound
Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models cites this paper.
Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models Unifying Human and Statistical Evaluation for Natural Language Generation
Reference 69
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T22:57:01.677969Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 01dd2b39-8eb4-41da-b6f0-1bbb73b79f8b · inbound
Glimpse: Enabling White-Box Methods to Use Proprietary Models for Zero-Shot LLM-Generated Text Detection cites this paper.
Glimpse: Enabling White-Box Methods to Use Proprietary Models for Zero-Shot LLM-Generated Text Detection Unifying Human and Statistical Evaluation for Natural Language Generation
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T14:56:47.803073Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f6725b2b-cd91-477e-b2ef-ad3298e166ca · inbound
Your Language Model Can Secretly Write Like Humans: Contrastive Paraphrase Attacks on LLM-Generated Text Detectors cites this paper.
Your Language Model Can Secretly Write Like Humans: Contrastive Paraphrase Attacks on LLM-Generated Text Detectors Unifying Human and Statistical Evaluation for Natural Language Generation
Reference 2019
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:22:30.546016Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b7bc65c1-2fd2-4225-81fa-9c66fd57a8a7 · inbound
Lightweight Stylistic Consistency Profiling: Robust Detection of LLM-Generated Textual Content for Multimedia Moderation cites this paper.
Lightweight Stylistic Consistency Profiling: Robust Detection of LLM-Generated Textual Content for Multimedia Moderation Unifying Human and Statistical Evaluation for Natural Language Generation
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T23:31:58.506188Z
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.