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Paper Citation Record · LEDGER

RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2404.19543.

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

pith.paper-citation-record.v1
2404.19543 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T16:29:56.672218Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T02:15:55.476828Z

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 72c81764-0e9d-4a25-84a6-a710b9787c9f · inbound

A Survey on Retrieval-Augmented Text Generation for Large Language Models cites this paper.

A Survey on Retrieval-Augmented Text Generation for Large Language Models RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-24T02:15:55.479275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-24T02:15:05.379583Z digest=sha256:9ba88e8289280b230d87960da74d58e212e27056ea79f149bdba0bfc91f3b4b4

Observation ae482ade-b626-41d0-bc39-e54b7dd82ebd · inbound

Retrieval-Augmented Generation for Natural Language Processing: A Survey cites this paper.

Retrieval-Augmented Generation for Natural Language Processing: A Survey RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-05-23T23:08:35.674755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-23T23:06:41.081461Z digest=sha256:c63496f4d4b55bb21d117df2111e30c932913660c24e235d2e93491a46e3f847

Observation 873ae1a7-4367-45ed-ad39-549dcb856795 · inbound

Large Action Models: From Inception to Implementation cites this paper.

Large Action Models: From Inception to Implementation RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-11T16:29:56.672218Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T16:29:56.672218Z digest=sha256:8ea6272e62ffae764d4242605369c7a3e4fe015b25baff6b99e89af01e118b24

Observation f5e1d008-f467-4829-9183-a60ffe7af107 · inbound

ArchRAG: Attributed Community-based Hierarchical Retrieval-Augmented Generation cites this paper.

ArchRAG: Attributed Community-based Hierarchical Retrieval-Augmented Generation RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-23T03:32:28.531643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-23T03:28:13.313028Z digest=sha256:b1b0d60a9a4ac2cb3c573697e423382c70759410526f2f7498fe3833f70d35c4

Observation 9c7c0c2f-07b5-4fed-9bc4-b16b3d191679 · inbound

In-depth Analysis of Graph-based RAG in a Unified Framework cites this paper.

In-depth Analysis of Graph-based RAG in a Unified Framework RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-23T01:37:22.443381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-23T01:36:25.057478Z digest=sha256:3a3b915e7877488957c228bd27bccb3d3f497f8a0d7458d92cf6d998eff49a7c

Observation e14c52f8-2136-4a9b-853d-371556c5e2db · inbound

DoctorRAG: Medical RAG Fusing Knowledge with Patient Analogy through Textual Gradients cites this paper.

DoctorRAG: Medical RAG Fusing Knowledge with Patient Analogy through Textual Gradients RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T14:15:58.022514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:15:58.022514Z digest=sha256:23f42e61b9d5b34809d9c30690466c6999df56cfeb183a5a5ac3100dabcab2e6

Observation f78dddaa-0316-4291-bcff-be0ce06a40e8 · inbound

RAGOps: Operating and Managing Retrieval-Augmented Generation Pipelines cites this paper.

RAGOps: Operating and Managing Retrieval-Augmented Generation Pipelines RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T11:07:10.545900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:07:10.545900Z digest=sha256:643b0a14d321a0b0ef00bc26c5c1b7fc86cf6d9c0739b71b94a909fa537de0f9

Observation 38966540-b352-470c-8eef-437c401bb2da · inbound

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG cites this paper.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T12:09:54.561639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:54.561639Z digest=sha256:fb68b03cf16c2d026796a05abf03d8bd70cf628558c7225067ed4f42714b3a88

Observation 0e650bbb-8505-4fa3-ba35-d669135f04bd · inbound

KERAG_R: Knowledge-Enhanced Retrieval-Augmented Generation for Recommendation cites this paper.

KERAG_R: Knowledge-Enhanced Retrieval-Augmented Generation for Recommendation RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T19:23:48.861410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:23:48.861410Z digest=sha256:ce58fc7228399be4aba62d3ab5ca9cf660c20806cf29adc160b4f7d479440e22

Observation 6f70bcd8-77ce-4697-ba8e-cf1f52c8210f · inbound

Adaptive Query Routing: A Tier-Based Framework for Hybrid Retrieval Across Financial, Legal, and Medical Documents cites this paper.

Adaptive Query Routing: A Tier-Based Framework for Hybrid Retrieval Across Financial, Legal, and Medical Documents RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-10T14:45:40.666030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-10T14:42:00.856705Z digest=sha256:5125e2b46602397232541d38fea012f2221bc4afaca7159102e07332de7b6110

Observation 63e8ce3b-14bd-4636-b68c-0a36aa480d5e · inbound

EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval cites this paper.

EHRAG: Bridging Semantic Gaps in Lightweight GraphRAG via Hybrid Hypergraph Construction and Retrieval RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing

Reference 290

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T05:56:11.437968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-10T05:43:04.813867Z digest=sha256:b5ff56c7fba837b7eb3d0b33dd09cfcfbcbeaef4bb946ae124ab37de175b6066

Observation 439aab74-36a3-4761-ae73-4d84e12bdca1 · inbound

PIER: Physics-Informed Environmental Retrieval for Time-Series Modeling cites this paper.

PIER: Physics-Informed Environmental Retrieval for Time-Series Modeling RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-01T10:29:16.199113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T10:29:16.199113Z digest=sha256:f33f37caffa9d4566086cac233228e79e7fbc3b2b4ff6829963bd94c102d4f40