Paper Citation Record · LEDGER

Extracting Document Relations from Search Corpus by Marginalizing over User Queries

As of 19 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2507.10726.

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

pith.paper-citation-record.v1
2507.10726 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:31:22.326342Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

14 of 14 outbound references displayed

verified exact2
verified fuzzy10
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 091ab533-ecc2-49ef-a24f-553195e39174 · outbound

This paper cites Focus+ context edge bundling for network visualization.

Extracting Document Relations from Search Corpus by Marginalizing over User Queries Focus+ context edge bundling for network visualization

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:31:24.644072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8fc04050-3a27-4b90-a5ab-3c54b44d824f · outbound

This paper cites Business insights using rag–llms: a review and case study.

Extracting Document Relations from Search Corpus by Marginalizing over User Queries Business insights using rag–llms: a review and case study

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:31:24.410408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 84f90017-d912-4d3c-a803-fd509ac27027 · outbound

This paper cites Towards Improving the Explainability of Text-based Information Retrieval with Knowledge Graphs.

Extracting Document Relations from Search Corpus by Marginalizing over User Queries Towards Improving the Explainability of Text-based Information Retrieval with Knowledge Graphs

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:31:22.693050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c5472ff5-9fb4-40db-96a3-cffe1309d0c3 · outbound

This paper cites Document AI: Benchmarks, Models and Applications.

Extracting Document Relations from Search Corpus by Marginalizing over User Queries Document AI: Benchmarks, Models and Applications

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T17:31:21.486130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66c1cd68-27a5-42c6-bc33-7cad5b0bd069 · outbound

This paper cites BERT: pre-training of deep bidirectional trans- formers for language understanding.

Extracting Document Relations from Search Corpus by Marginalizing over User Queries BERT: pre-training of deep bidirectional trans- formers for language understanding

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:31:24.209834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 52e7ca42-3b31-4d47-a85d-2ea10911b2c8 · outbound

This paper cites Dense passage retrieval for open-domain question answering.

Extracting Document Relations from Search Corpus by Marginalizing over User Queries Dense passage retrieval for open-domain question answering

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:31:24.037263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e03e546f-bad2-4225-8d67-a33ec3d3b310 · outbound

This paper cites Colbert: Efficient and effective passage search via contextualized late interaction over BERT.

Extracting Document Relations from Search Corpus by Marginalizing over User Queries Colbert: Efficient and effective passage search via contextualized late interaction over BERT

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:31:23.850229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e1149833-0375-4a40-8787-c97b8fbccddc · outbound

This paper cites BART: denoising sequence-to- sequence pre-training for natural language generation, trans- lation, and comprehension.

Extracting Document Relations from Search Corpus by Marginalizing over User Queries BART: denoising sequence-to- sequence pre-training for natural language generation, trans- lation, and comprehension

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:31:23.676807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7b036c93-ea18-41ce-b4e6-05e78c7ee8f6 · outbound

This paper cites Retrieval-augmented genera- tion for knowledge-intensive NLP tasks.

Extracting Document Relations from Search Corpus by Marginalizing over User Queries Retrieval-augmented genera- tion for knowledge-intensive NLP tasks

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:31:23.524124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 28637bc9-4566-4707-a8ef-9b5c60a6c953 · outbound

This paper cites an unresolved cited work.

Extracting Document Relations from Search Corpus by Marginalizing over User Queries Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-06T17:31:23.325336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8fde8e21-59bd-44bb-a4f1-ec4caba8d73e · outbound

This paper cites Fact or fiction: Verifying scientific claims.

Extracting Document Relations from Search Corpus by Marginalizing over User Queries Fact or fiction: Verifying scientific claims

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:31:23.169334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4b05caa9-7e77-4c7d-9479-630005c4af93 · outbound

This paper cites RAGViz: Diagnose and Visualize Retrieval-Augmented Generation.

Extracting Document Relations from Search Corpus by Marginalizing over User Queries RAGViz: Diagnose and Visualize Retrieval-Augmented Generation

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:31:22.496384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d8699031-d4a2-472b-8050-f06b8703fe24 · outbound

This paper cites Graph-based hierarchical relevance matching signals for ad- hoc retrieval.

Extracting Document Relations from Search Corpus by Marginalizing over User Queries Graph-based hierarchical relevance matching signals for ad- hoc retrieval

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:31:23.015622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4e172ebe-6f18-47d2-bcc2-8ba1e1b6251e · outbound

This paper cites Edge bundling in information visualization.

Extracting Document Relations from Search Corpus by Marginalizing over User Queries Edge bundling in information visualization

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:31:22.841246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.