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Paper Citation Record · LEDGER

GRM: Generative Relevance Modeling Using Relevance-Aware Sample Estimation for Document Retrieval

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2306.09938.

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

pith.paper-citation-record.v1
2306.09938 v1

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 2026-08-05T06:32:48.257954+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T23:33:47.315845Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T16:06:39.858255Z

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 0ea10c66-5043-42bc-b6c8-14ad1b0ccbf2 · inbound

TeaRAG: A Token-Efficient Agentic Retrieval-Augmented Generation Framework cites this paper.

TeaRAG: A Token-Efficient Agentic Retrieval-Augmented Generation Framework GRM: Generative Relevance Modeling Using Relevance-Aware Sample Estimation for Document Retrieval

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-03T23:33:47.315845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T23:33:47.315845Z digest=sha256:6bc488de96a9c5ac51a23b723a257f469c766738fa241e359b049d79290b38b9

Observation 5baaee4f-0f0c-4abe-bc09-cb5852eb397c · inbound

When More Reformulations Hurt: Avoiding Drift using Ranker Feedback cites this paper.

When More Reformulations Hurt: Avoiding Drift using Ranker Feedback GRM: Generative Relevance Modeling Using Relevance-Aware Sample Estimation for Document Retrieval

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:06:39.898410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-09T18:40:35.840350Z digest=sha256:098c272c1f660ba7416a37b45c54337ea4a7e94bcac39940aef192bb1775d4f4