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Paper Citation Record · LEDGER

RetrievalSum: A Retrieval Enhanced Framework for Abstractive Summarization

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2109.07943.

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

pith.paper-citation-record.v1
2109.07943 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:01:54.982063Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T02:22:25.494380Z

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 77adb642-29e7-44c7-a9dd-2fb944a61f54 · inbound

Towards Optimizing a Retrieval Augmented Generation using Large Language Model on Academic Data cites this paper.

Towards Optimizing a Retrieval Augmented Generation using Large Language Model on Academic Data RetrievalSum: A Retrieval Enhanced Framework for Abstractive Summarization

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-12T21:40:02.326300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T21:40:02.326300Z digest=sha256:bd9ceb3d67e7a8990a3e1bbff0cb9a46c2170ed1cbc933e404e2379e5c08f10c

Observation 514ac80d-ad48-4681-8af6-92e1e7bbad7d · inbound

RELexED: Retrieval-Enhanced Legal Summarization with Exemplar Diversity cites this paper.

RELexED: Retrieval-Enhanced Legal Summarization with Exemplar Diversity RetrievalSum: A Retrieval Enhanced Framework for Abstractive Summarization

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-10T15:25:30.418103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:25:30.418103Z digest=sha256:ac5994db70c4edd9f67e20af6319e2219ae744c41cd21dfb6656c43771e69599

Observation 73b2510c-69e6-41c7-8367-12bda890f0c0 · inbound

Supervising the search process produces reliable and generalizable information-seeking agents cites this paper.

Supervising the search process produces reliable and generalizable information-seeking agents RetrievalSum: A Retrieval Enhanced Framework for Abstractive Summarization

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-23T02:22:25.496881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-23T02:18:27.204122Z digest=sha256:2e4322b11bb8e34689ef7dbc9ca015928cb65e660d231787909ac65fed6f50b6

Observation 27152637-92fa-49d8-8f57-b2c00ee115c5 · inbound

A Unified Retrieval Framework with Document Ranking and EDU Filtering for Multi-document Summarization cites this paper.

A Unified Retrieval Framework with Document Ranking and EDU Filtering for Multi-document Summarization RetrievalSum: A Retrieval Enhanced Framework for Abstractive Summarization

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-16T11:01:54.982063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:01:54.982063Z digest=sha256:dda72a3c3fe2687da1483228e63864e386aee2115039343b137f2b5180449c79

Observation c72a4546-48c0-4bf7-9493-94781850c48c · inbound

Magic Mushroom: A Customizable Benchmark for Fine-grained Analysis of Retrieval Noise Erosion in RAG Systems cites this paper.

Magic Mushroom: A Customizable Benchmark for Fine-grained Analysis of Retrieval Noise Erosion in RAG Systems RetrievalSum: A Retrieval Enhanced Framework for Abstractive Summarization

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T10:57:26.869269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:57:26.869269Z digest=sha256:a79b1e70501de083606700ffb78d42f6b7e5e4cffdf58cda34df6bad9b9b4cb5