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Paper Citation Record · LEDGER

ExpandR: Teaching Dense Retrievers Beyond Queries with LLM Guidance

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.17057.

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

pith.paper-citation-record.v1
2502.17057 v3

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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T17:22:46.110498Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T18:11:43.037591Z

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 1fc7fecb-ab9c-4daf-919b-f085a4a625df · inbound

Query Expansion in the Age of Pre-trained and Large Language Models: A Comprehensive Survey cites this paper.

Query Expansion in the Age of Pre-trained and Large Language Models: A Comprehensive Survey ExpandR: Teaching Dense Retrievers Beyond Queries with LLM Guidance

Reference 121

Resolution
verified exact
arxiv_id, observed 2026-05-18T18:11:43.039675Z

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=2026-05-18T18:07:33.612858Z digest=sha256:4509040188a0ec0a3b712aa149abe902ca1f08215976e5567d79b21599689e9d

Observation df739bc4-f55b-4083-9471-e92fa2b5702e · inbound

MPR-CiteG: Enhancing RAG with Multi-Portfolio Retrieval and Citation-Grounded Generation cites this paper.

MPR-CiteG: Enhancing RAG with Multi-Portfolio Retrieval and Citation-Grounded Generation ExpandR: Teaching Dense Retrievers Beyond Queries with LLM Guidance

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-01T17:22:46.110498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T17:22:46.110498Z digest=sha256:754874e4802f059bf51b270dce3fd816f11160635e097e5ac602c80eb72d69c1