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Paper Citation Record · LEDGER

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation

As of 10 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2607.11159.

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

pith.paper-citation-record.v1
2607.11159 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T06:36:34.161979Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

37 of 37 outbound references displayed

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  • verified fuzzy0
  • unresolved37
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 93fce50e-347c-4206-9459-e5b85a07bc17 · outbound

This paper cites H otpot QA : A Dataset for Diverse, Explainable Multi-hop Question Answering.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation H otpot QA : A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 1

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:3435716b0232b7249f5bbef8e09eab046b8127f842dd525df655757ea83b9dbd

Observation b78a537b-adde-4a18-ad4f-b85741fb7bc1 · outbound

This paper cites MultiHop-.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation MultiHop-

Reference 2

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:3ba78e7a2ad372bbf5933a23a9584cd874d3412af9763f326ecd5006f85a1b31

Observation 4bb5ab33-8c72-4556-a83c-e73e94845ce9 · outbound

This paper cites Proceedings of the ACM Web Conference 2025 (TheWebConf 2025) , year =.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation Proceedings of the ACM Web Conference 2025 (TheWebConf 2025) , year =

Reference 3

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:3d955d6d3b0916a5aadf6fb8254fcf1945a393bcddad8475cd222b692e65253e

Observation 0cad4a7f-4492-4ac8-bd57-69ef17ca42d5 · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 4

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:057e30c5ef63a1409726d7ddcc17f115185b9f2c4ba865ff62ef0d116e630edc

Observation 0ea22c4f-5160-4843-95be-2bc37a9a49f2 · outbound

This paper cites From Local to Global: A Graph RAG Approach to Query-Focused Summarization.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation From Local to Global: A Graph RAG Approach to Query-Focused Summarization

Reference 5

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:a2f6e2162126fad654dfda4587a25082a648129b89757f04994e090add32cc20

Observation 75d52cc2-db00-45ce-bd98-a13fa1834a5d · outbound

This paper cites LightRAG: Simple and Fast Retrieval-Augmented Generation.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation LightRAG: Simple and Fast Retrieval-Augmented Generation

Reference 6

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:6c2658f9ea12116cbb6945805480c5df0b8f99ef2f33d054bdc4ce43e32761c3

Observation ffdcfdc8-b34b-4c3c-9efe-d31a45560ad5 · outbound

This paper cites Stanford Center for Research on Foundation Models.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation Stanford Center for Research on Foundation Models

Reference 7

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:a82c9de3347572bec06110ede7a6210f64c5c0a48a228076acc9404598ad699f

Observation d9d404e5-36a7-4f57-938f-d30ac129ce22 · outbound

This paper cites arXiv preprint arXiv:2308.10792 , year=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation arXiv preprint arXiv:2308.10792 , year=

Reference 8

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:7279f6b47c1522e3156c490e567955be2b47f3248dd244244818aba39d1c5c50

Observation 54a2a265-5995-40bb-8f78-f7b0aa9565ae · outbound

This paper cites Proceedings of the 2021 conference on empirical methods in natural language processing , pages=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation Proceedings of the 2021 conference on empirical methods in natural language processing , pages=

Reference 9

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:842593cc759ad9fea4abed1e5ab28a3e4f78c5f1e229e3f9f27e6987c314be6b

Observation a5d1eb48-e4ee-420c-8781-c083e88461c3 · outbound

This paper cites International conference on machine learning , pages=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation International conference on machine learning , pages=

Reference 10

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:a611d0a222f59becc2b3880735a9b3262f6eee716d38d41c8a1ff78b9db09d55

Observation 9ceaa223-cafe-4660-9311-98b45ce65916 · outbound

This paper cites SIGIR 2020 , pages=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation SIGIR 2020 , pages=

Reference 11

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:4939f4b2e7126c372d1a923e6055d1e46b24a8d2ffa62307d647066c02c20597

Observation 49cfde17-a9fb-4049-a946-9375f82bb826 · outbound

This paper cites International Conference on Learning Representations , year=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation International Conference on Learning Representations , year=

Reference 12

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:ed47c1b9bbbafd168a78f3f32a385c0f25cec4a6e52966e33a88a435082ca83c

Observation b07ed5db-9d19-4a2b-bd20-f0df34542c4a · outbound

This paper cites ArXiv , year=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation ArXiv , year=

Reference 13

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:d1f4b37d16e65a0329d8e10bc09eee8c1ebefb38172d990858a91789428f633f

Observation e8f7db74-1b6a-4572-a128-a16cb7a63c5d · outbound

This paper cites ArXiv , year=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation ArXiv , year=

Reference 14

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:705fddb727231912092fbf81f7c6520421831b42db9ccd7c7753644bfd5db6c6

Observation a97cd993-93f6-481e-a369-28f1728cf301 · outbound

This paper cites Extended Semantic Web Conference , year=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation Extended Semantic Web Conference , year=

Reference 15

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:69b787066073c4f999beb6c40dd3175e4440e50147d12ef9ee3abcb3ef255c98

Observation 28ea9b26-8c70-4e68-be5e-2d6cb897381b · outbound

This paper cites IEEE transactions on pattern analysis and machine intelligence , volume=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation IEEE transactions on pattern analysis and machine intelligence , volume=

Reference 16

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:e92de2c7e0c8289c3aa8e1bbd45e1f04fb108a43217f4eb7c1d4ff9cf4e8eb07

Observation cbe38bb6-3d11-42d0-b640-88193d1af913 · outbound

This paper cites 2008 , publisher=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation 2008 , publisher=

Reference 17

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:51299e7559de9cfda2487d0e13c1566095582c6cd52e0b67a105d303b5df61c9

Observation e3267131-06b0-44cb-9a20-5014fc8a6da2 · outbound

This paper cites arXiv: Learning , year=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation arXiv: Learning , year=

Reference 18

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:e7ea54db3d25e780002b44f114b1ada86048ad2b71cf5ef9fcaecbc756765c16

Observation 151027db-1512-4aaa-97bf-4f29d3e5a8a4 · outbound

This paper cites C-Pack: Packed Resources For General Chinese Embeddings.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation C-Pack: Packed Resources For General Chinese Embeddings

Reference 19

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:25cf479fd91ad57b9270f9680025ca03d559346fa1148c14d12c15b8b0ad0bff

Observation f9f3fa90-d128-498d-b61f-8b2cad3c61e1 · outbound

This paper cites International conference on machine learning , pages=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation International conference on machine learning , pages=

Reference 20

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:2b1647af61c63bfd11872c3c4c362a22101456cd2df58e96db4c081da33736f2

Observation 501ad13e-c26a-4890-9c70-9386a219259b · outbound

This paper cites Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 21

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:417e5abc71342594459eff33b6eaac6f0f50b780cd186392ab061332c3acb411

Observation d466c951-b5da-432e-9c30-29c248852077 · outbound

This paper cites Foundations and Trends.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation Foundations and Trends

Reference 22

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:e8a1869c24bef7477cc5825365416946f6e720883facd7e89bedce71b925ee9e

Observation a8f07510-00c4-46a8-9f14-ce2a955fd162 · outbound

This paper cites , author=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation , author=

Reference 23

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:0ab2773f279b36b2502396f5941fc23fe8fb4fbcaf6a30df104927e3563fb99a

Observation 331701fb-b201-4a95-85c5-26508c598090 · outbound

This paper cites EACL 2024 Demos , pages=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation EACL 2024 Demos , pages=

Reference 24

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:c8652a32eca08ed5d94075e3190c505ce6fa0a8eaa1c09c9bb45147635939958

Observation d57ab34c-3540-473b-bbcc-de4a0049ec98 · outbound

This paper cites Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval , pages=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval , pages=

Reference 25

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:853b1725e409b4e8c7586bf47bd2dbe4a8b4cf115c9b3c09373ec5bbc893fb2f

Observation 8432528b-1db6-4117-ad8d-7953217e072a · outbound

This paper cites Retrieval-Augmented Generation for AI-Generated Content: A Survey.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation Retrieval-Augmented Generation for AI-Generated Content: A Survey

Reference 26

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:390e529745f78d2d182160916463f4064d03ff2ebc50f966e576fe4cf0622386

Observation 748f67c1-9798-4872-ae72-a470afcd5e48 · outbound

This paper cites Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 27

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:324bd08c239efbd17714c13267e868f63492e489845bcb880791272313a4e8a4

Observation 68815c75-f8a4-4721-a0e6-9218a28705eb · outbound

This paper cites KDD 2024 , pages=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation KDD 2024 , pages=

Reference 28

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:72500e88eb8d7ead9ce90dd2f5b6f9a24a876ef79e4c6fc5e02daed310602859

Observation 73f5c1eb-8430-48b4-97d5-58dddfa22028 · outbound

This paper cites Retrieval-Augmented Generation with Graphs (GraphRAG).

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation Retrieval-Augmented Generation with Graphs (GraphRAG)

Reference 29

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:dbdffcdf5dfa1d180a732e7bda89691de2996445c2785c5b8cf96e02aa680ed7

Observation 8eb84b8a-7152-4544-bea0-65c346692661 · outbound

This paper cites arXiv preprint arXiv:2502.14902 , year=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation arXiv preprint arXiv:2502.14902 , year=

Reference 30

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:d3757ff14539514aaa3387f8e1090bdb01018715ac64d8d71238889c6be85b23

Observation 2fba9105-9c77-48c6-a5a2-57717db9c906 · outbound

This paper cites MiniRAG: Towards Extremely Simple Retrieval-Augmented Generation.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation MiniRAG: Towards Extremely Simple Retrieval-Augmented Generation

Reference 31

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:46cc34dd99417e9e39b4806f78d61c9f6c0a1938a61fcee617094cbba08a46f8

Observation 7da806cc-6a9c-4c6a-8694-e050b4fc0ee4 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 32

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:90253509058cddc165540dc8eaaccb3a2d3db951c3697eb30dc4e2ec06fbca7d

Observation 2c463936-ce24-40a4-83d5-9932b2557610 · outbound

This paper cites GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning

Reference 33

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:659ce97f7a8ae6d549444d42f2df76c90c30d737274790e2419c232af34edaf0

Observation c8deb4af-82da-43f8-bdf0-990fd019bd4e · outbound

This paper cites Neural Subgraph Matching.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation Neural Subgraph Matching

Reference 34

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:41c3d725690a6ab5d72db0fe72f0f47d62cb08c714844b3025b52cfae3467d6d

Observation 28a6bea1-2464-4ce7-a8c0-328efde4dabf · outbound

This paper cites Proceedings of the AAAI conference on artificial intelligence , volume=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation Proceedings of the AAAI conference on artificial intelligence , volume=

Reference 35

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:9e9400eb11f421a8b043f1737c7e292e0dcc4e795938a8d2b7199da61d89cc9a

Observation be2f512d-4675-4ef4-a87c-b37f286b1c62 · outbound

This paper cites Proceedings of the 29th International Conference on Computational Linguistics , pages=.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation Proceedings of the 29th International Conference on Computational Linguistics , pages=

Reference 36

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:712cb949245b806e74b5d52e3b84ba41e09d281d1a3e8b901d347a0493cdd905

Observation 964d3dc8-70e2-4134-8b4f-a37fdfa13f10 · outbound

This paper cites GRAG: Graph Retrieval-Augmented Generation.

NGM-RAG: Neural Graph Matching based Retrieval-Augmented Generation GRAG: Graph Retrieval-Augmented Generation

Reference 37

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source=arxiv_source observed=2026-07-14T06:36:34.161979Z digest=sha256:92060ddc62144934eef44e7ff488cd6cee740a8d1eaad4b25d0165f537c3b48f

Pith citing papers

No inbound Pith citation observations are available.