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Paper Citation Record · LEDGER

DHP Benchmark: Are LLMs Good NLG Evaluators?

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2408.13704.

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

pith.paper-citation-record.v1
2408.13704 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T23:35:42.891112Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T17:35:44.094403Z

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 fe3adea1-8cde-4648-8674-774fcc8d3085 · inbound

A Survey on LLM-as-a-Judge cites this paper.

A Survey on LLM-as-a-Judge DHP Benchmark: Are LLMs Good NLG Evaluators?

Reference 168

Resolution
verified exact
arxiv_id, observed 2026-05-23T17:35:44.098558Z

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=2026-05-23T17:33:13.394338Z digest=sha256:63ee5f06c0fd48b4f50a0369fcd68d36a3ca1be4e67f4a296c787d35b6d9a934

Observation ba2eda73-8fe5-4972-a8bd-8add8a617f16 · inbound

The Science of Evaluating Foundation Models cites this paper.

The Science of Evaluating Foundation Models DHP Benchmark: Are LLMs Good NLG Evaluators?

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-07T23:35:42.891112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T23:35:42.891112Z digest=sha256:6439bbbf1977bd6369a0a4a2d2466b77b269bf30a8293363deeacb8eacf1e035

Observation e61eff3a-c10c-49e2-9088-3eae42c15491 · inbound

Semantic Needles in Document Haystacks: Sensitivity Testing of LLM-as-a-Judge Similarity Scoring cites this paper.

Semantic Needles in Document Haystacks: Sensitivity Testing of LLM-as-a-Judge Similarity Scoring DHP Benchmark: Are LLMs Good NLG Evaluators?

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:51:03.647068Z

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=arxiv_source observed=2026-05-10T04:31:53.825854Z digest=sha256:e20973f8df104ea22f4fd34c79c1119b3d966f3f6e907baafb39d502ba916b02