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Paper Citation Record · LEDGER

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data

As of 21 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2507.12425.

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

pith.paper-citation-record.v1
2507.12425 v1

Coverage vector

measured 22 of 22 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:51:56.340360Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

22 of 22 outbound references displayed

  • verified exact1
  • verified fuzzy3
  • unresolved18
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4a50a754-f07a-4efb-bd38-48b86a9d974f · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data On the Opportunities and Risks of Foundation Models

Reference 1

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no resolver link, observed 2026-08-06T16:51:54.554629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:54.554629Z digest=sha256:f444be7352ff68378aaad98b4b69c8f482a81f2be4c5f8851c00610598a447ae

Observation 58bcb85f-8e67-4414-ad9b-3048db5a08b8 · outbound

This paper cites Camelot: PDF Table Extraction for Humans.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data Camelot: PDF Table Extraction for Humans

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-06T16:51:57.290635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T16:51:54.626707Z digest=sha256:9658b6ca418d7e05e368b405e26ed18b095bde2b1d0e68b0f04d34382e5516e5

Observation 4d33291f-d523-477f-83b5-bc62baf37625 · outbound

This paper cites PaLM: Scaling Language Modeling with Pathways.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data PaLM: Scaling Language Modeling with Pathways

Reference 3

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no resolver link, observed 2026-08-06T16:51:54.709081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:54.709081Z digest=sha256:da95a675c04c09e29fbc37c8655b33a75b0f3d3a4a9c81fed05384930c3207e6

Observation 83caded3-7bbf-4af8-86f1-6e5064cec011 · outbound

This paper cites Precise Zero-Shot Dense Retrieval without Relevance Labels.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data Precise Zero-Shot Dense Retrieval without Relevance Labels

Reference 4

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no resolver link, observed 2026-08-06T16:51:54.828394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:54.828394Z digest=sha256:9ebf5134ffb593fbb655cb3946228c13f3915bb0733e60f0d0f2e7ece04a23a1

Observation 4a2982a0-c041-4437-815d-9ab485f12109 · outbound

This paper cites REALM: Retrieval-Augmented Language Model Pre-Training.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data REALM: Retrieval-Augmented Language Model Pre-Training

Reference 5

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no resolver link, observed 2026-08-06T16:51:54.914720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:54.914720Z digest=sha256:b4496e372bd238337f1047ac78434de573f1f01012445ecabecf978ed40ef2cb

Observation 90f874fd-0797-42b5-8f4c-442d6bdef2cf · outbound

This paper cites TAPAS: Weakly Supervised Table Parsing via Pre-training.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data TAPAS: Weakly Supervised Table Parsing via Pre-training

Reference 6

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no resolver link, observed 2026-08-06T16:51:55.034701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:55.034701Z digest=sha256:8795936ab79b942b912538a407ff1fc7e2aa9a3cb295137fa715fa8fb244cbb5

Observation 963e1bde-9d0e-423b-8306-76cdbfff8035 · outbound

This paper cites Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering

Reference 7

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unresolved
no resolver link, observed 2026-08-06T16:51:55.127079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:55.127079Z digest=sha256:77f603d260e0b74bf99ecced982fc18c6f184f4a1d8c9d8a5e201b51241deb38

Observation a0dd0afd-c68c-4849-b030-5293374ad000 · outbound

This paper cites Dense Passage Retrieval for Open-Domain Question Answering.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data Dense Passage Retrieval for Open-Domain Question Answering

Reference 8

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no resolver link, observed 2026-08-06T16:51:55.218679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:55.218679Z digest=sha256:35cc9d616ab7b552c1650d87190eabb04bd536597c4f1313397442033ac53dfd

Observation 639c193e-40de-4ebd-a2c1-f56ebb21d722 · outbound

This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Reference 9

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no resolver link, observed 2026-08-06T16:51:55.295309Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:55.295309Z digest=sha256:8ed272cd84dc6ee7269bcb54adfccba94919a3bf8623e4598f51ac3d400d765f

Observation ca763828-ddb3-4556-9d9e-02d67dbf9dd4 · outbound

This paper cites Passage Re-ranking with BERT.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data Passage Re-ranking with BERT

Reference 10

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no resolver link, observed 2026-08-06T16:51:55.359586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:55.359586Z digest=sha256:57835c9ddf9a875444472a27529fe0a56f567483f80fdf83def235155b9e8c82

Observation 18546d44-131f-4f4c-800c-e22b8f679efd · outbound

This paper cites GPT-4 Technical Report.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data GPT-4 Technical Report

Reference 11

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no resolver link, observed 2026-08-06T16:51:55.395998Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:55.395998Z digest=sha256:55b9c1bc03458101a34a535c4dffc6eeda0ae78c1aac0a85d4e87854224037e0

Observation de302584-657b-4b03-b190-fa2ba2b8741c · outbound

This paper cites Ensemble of MRR and NDCG models for Visual Dialog.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data Ensemble of MRR and NDCG models for Visual Dialog

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-08-06T16:51:56.537768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T16:51:55.479624Z digest=sha256:3d8dc3c04461584865cfef361ee611583e49cd3208d20da0d5388d043e45bc0d

Observation 24d6a46a-10b0-4296-986f-c98f6911c08f · outbound

This paper cites Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation

Reference 13

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no resolver link, observed 2026-08-06T16:51:55.590706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:55.590706Z digest=sha256:63995de267df0f6c052dda72eb9891af2d39147d01e24f06d361ea985b87880f

Observation 52c5e50c-dcb4-4e49-8f21-9696f7791ae5 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 14

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no resolver link, observed 2026-08-06T16:51:55.685709Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:55.685709Z digest=sha256:00cd3dd4245e35eaceacb9b9cba41d2d2833981dddadf30b4306d42108259a67

Observation 1d50bdcd-76f0-4fc4-a9ae-125571deb0b3 · outbound

This paper cites Robertson and H.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data Robertson and H

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-06T16:51:57.049797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T16:51:55.763188Z digest=sha256:93b097fca98faaabf10ae9c3472cf693ae61fadb3b1752c6a455d3d1cb8fa93c

Observation 082284b8-01ee-418a-9c47-b53966abb90e · outbound

This paper cites Reflexion: Language Agents with Verbal Reinforcement Learning.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data Reflexion: Language Agents with Verbal Reinforcement Learning

Reference 16

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:55.838603Z digest=sha256:3b63563281d6ff5ec0d35374448dc24680e23c27ae9144e174a31f7c0e947d4e

Observation 1e67dbc6-cd93-46bf-807a-f18329c29e76 · outbound

This paper cites spaCy: Industrial-Strength Natural Language Processing.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data spaCy: Industrial-Strength Natural Language Processing

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:51:56.749658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-06T16:51:55.888536Z digest=sha256:2d2427f301b50522f1a70066c0daa6949575fdaf0a9da3adb43c6d6e042af0e9

Observation 11f9f7f6-3ea9-44f1-a65c-96dfd6e9a0c9 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data LLaMA: Open and Efficient Foundation Language Models

Reference 18

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source=pdf_text observed=2026-08-06T16:51:55.979590Z digest=sha256:073db2f445dd90cf076633bf0049f02f800d033d986ed4ea771aeab46a9625f1

Observation 82c1a694-5bcd-467d-af74-2018a87a2c15 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data ReAct: Synergizing Reasoning and Acting in Language Models

Reference 19

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source=pdf_text observed=2026-08-06T16:51:56.079892Z digest=sha256:4c42c4ae645ddf0afdfefd2810906a0ec5e41414787d67c28caa56ebfaae1f5a

Observation ef467f1a-6e04-4737-891d-deb5eaae908a · outbound

This paper cites TURL: Table Understanding through Representation Learning.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data TURL: Table Understanding through Representation Learning

Reference 20

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source=pdf_text observed=2026-08-06T16:51:56.162436Z digest=sha256:a6b7bb4378d570279baf8e4edda06a0865d1a2bcc7b5060d270aef9905e0b8c2

Observation c51d580f-deaf-4432-9376-bd07e563f21a · outbound

This paper cites Augmented Language Models: a Survey.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data Augmented Language Models: a Survey

Reference 21

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:56.243044Z digest=sha256:c46fd86f9558729b737c26fc9f171684447bbd520cb8a551e45aa8c4dbe737bf

Observation b0d0f173-d2a1-4a3c-9e44-81455c679471 · outbound

This paper cites ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT.

Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT

Reference 22

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unresolved
no resolver link, observed 2026-08-06T16:51:56.340360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:51:56.340360Z digest=sha256:b1f04bbadb94f7c91c1bbed36e4a2482e68700560962a542c35d54bd38ee2c58

Pith citing papers

No inbound Pith citation observations are available.