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Paper Citation Record · LEDGER

GPR: Empowering Generation with Graph-Pretrained Retriever

As of 8 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2506.00261.

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

pith.paper-citation-record.v1
2506.00261 v2

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:13:02.136813Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

24 of 24 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved20
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 97926a7d-49b0-4cbe-8565-79bf8f7fb20d · outbound

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

GPR: Empowering Generation with Graph-Pretrained Retriever Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:59.824845Z digest=sha256:1867eca6f15a71d5a53805eccc5fe52ffdcd2c51a45d46338535446ff114e7eb

Observation 70aa4c1f-0dc6-4973-aec9-f01f7fcbf45e · outbound

This paper cites GRAG: Graph Retrieval-Augmented Generation.

GPR: Empowering Generation with Graph-Pretrained Retriever GRAG: Graph Retrieval-Augmented Generation

Reference 6

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:13:00.097322Z digest=sha256:d1a3d9d25637e4ec19bcfe15abda8f74cee8336cbd764699510f062103801a95

Observation 53a39ea2-516a-40b8-b208-2c7e76d9b9ac · outbound

This paper cites Simple Is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation.

GPR: Empowering Generation with Graph-Pretrained Retriever Simple Is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation

Reference 7

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source=pdf_text observed=2026-08-07T12:13:00.201806Z digest=sha256:ae6071471e7a493c38ae094c6d03fb5a0d826119267bb64fbe4293ee970f5ca0

Observation 3610ce65-58c9-4da4-959c-59d39e4e3fc8 · outbound

This paper cites Graph Reasoning for Question Answering with Triplet Retrieval.

GPR: Empowering Generation with Graph-Pretrained Retriever Graph Reasoning for Question Answering with Triplet Retrieval

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:13:00.332779Z digest=sha256:f9ba76bf27c065066fdc798f1f8442835459599b13b09700be89fc8a52d1b90a

Observation fa7c700b-5e6f-4100-861d-25e37f480757 · outbound

This paper cites Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning.

GPR: Empowering Generation with Graph-Pretrained Retriever Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:13:00.673773Z digest=sha256:caf7eae0582f98772fce9de57ac6b53c2ff2c2782b5d78c545f6557789ec71f8

Observation 367c1c31-137b-4f5f-a3b2-1e57e96c502a · outbound

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

GPR: Empowering Generation with Graph-Pretrained Retriever GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:13:00.775082Z digest=sha256:fb8bf9346a33932f5e1b3f0afa3cc53112a57f9b90d6f5ab44484298542a3593

Observation d3f471da-c0b6-4d0e-ad85-747509f79519 · outbound

This paper cites Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering.

GPR: Empowering Generation with Graph-Pretrained Retriever Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:13:00.885821Z digest=sha256:be56e7c0c10f3b9dcb614c6a8e1f8e865ffbf31c5f27fb4c659efbce33d44f24

Observation 6b076808-df74-43ec-b6c7-251ba70d1935 · outbound

This paper cites Graph Retrieval-Augmented Generation: A Survey.

GPR: Empowering Generation with Graph-Pretrained Retriever Graph Retrieval-Augmented Generation: A Survey

Reference 14

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:13:01.207797Z digest=sha256:f704e35ddd14e3e5d3b03b92cb415e8dd0a5a9201c7a55fc696dae1c7e484432

Observation bcaccb7b-d96c-481c-9a02-f1942402a951 · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

GPR: Empowering Generation with Graph-Pretrained Retriever DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:13:01.293822Z digest=sha256:9786761dbf69706f2cb2b7df1caa1ee3a5421074c7ff61c7b5bf491acb6b85b2

Observation 95fd2b68-7112-45bc-9b0a-4d69127c540e · outbound

This paper cites The Web as a Knowledge-base for Answering Complex Questions.

GPR: Empowering Generation with Graph-Pretrained Retriever The Web as a Knowledge-base for Answering Complex Questions

Reference 16

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:13:01.392760Z digest=sha256:f71f6fd646b975667ce47fa5014ecf657e3482d0df0a2a571296ba1163768da1

Observation cdc9dfcd-8861-48db-a5ee-441e5310f6ed · outbound

This paper cites A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models.

GPR: Empowering Generation with Graph-Pretrained Retriever A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models

Reference 17

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:13:01.544584Z digest=sha256:672a60a5d7a4b9dd45f58b25112248719e189e843712b0162d77f1aa6239386e

Observation eaafe864-4e83-4f28-b7a7-52b9db216fd7 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

GPR: Empowering Generation with Graph-Pretrained Retriever Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:13:01.672305Z digest=sha256:4fcb2332feb563646345c53cf3b1997cb969928f9396105980b7c9e160462733

Observation d79d1eb8-7a70-4ca9-843e-f76094eafb6d · outbound

This paper cites Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models.

GPR: Empowering Generation with Graph-Pretrained Retriever Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:13:01.928369Z digest=sha256:5566ee058c4d8a991ac8c3f6c9d6dabecfb19d500a835f2c0a1ac2dee623f58e

Observation 26f6aa2f-b6f3-42a9-b533-f03c3d746b7f · outbound

This paper cites B Experiment Details Datasets.

GPR: Empowering Generation with Graph-Pretrained Retriever B Experiment Details Datasets

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:13:03.333644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:13:02.002113Z digest=sha256:087da781455adf64bcb59d1cab882330c4c84a6974afd1fc3fbcf1f7b82128d9

Observation 4bf68f7e-0f72-4c81-bf4e-2bbb873894b4 · outbound

This paper cites Pretraining is conducted for 5 epochs using AdamW (Loshchilov and Hutter, 2017), with a batch size of 512 and a learning rate of 2e-5.

GPR: Empowering Generation with Graph-Pretrained Retriever Pretraining is conducted for 5 epochs using AdamW (Loshchilov and Hutter, 2017), with a batch size of 512 and a learning rate of 2e-5

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:13:03.141443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:13:02.052058Z digest=sha256:ab42fe5a5890616f4d785453478db79a2a9ae172eda6add9d6130046587f7b86

Observation 7257f8eb-49dd-4b27-8a6c-9774f0b70da2 · outbound

This paper cites C Potential Risk Although GPR demonstrates strong performance, it is still possible for the retrieved results to reflect biases.

GPR: Empowering Generation with Graph-Pretrained Retriever C Potential Risk Although GPR demonstrates strong performance, it is still possible for the retrieved results to reflect biases

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:13:02.697120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:13:02.136813Z digest=sha256:7ec18b3d4c7750eadb972a3835527c76d6138091d77bf09d7770d27582f5fd1f

Observation 42fac3f4-afe1-4a04-a6d4-7673c2cd9d5e · outbound

This paper cites In Proceedings of the 2008 ACM SIG- MOD international conference on Management of data, pages 1247–1250.

GPR: Empowering Generation with Graph-Pretrained Retriever In Proceedings of the 2008 ACM SIG- MOD international conference on Management of data, pages 1247–1250

Reference 2008

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:13:03.665696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:12:59.441239Z digest=sha256:ca5c06a04bf3813e15e74479ec0a33c283e0a8a5107f7503e1827076a150dcc9

Observation 2a461539-f2d3-49cc-a6ed-847040df1902 · outbound

This paper cites Decoupled Weight Decay Regularization.

GPR: Empowering Generation with Graph-Pretrained Retriever Decoupled Weight Decay Regularization

Reference 2017

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source=pdf_text observed=2026-08-07T12:13:00.477098Z digest=sha256:8569be04822b159acb9d222ae2a45268de22c48dac2e451a08a54420b402a2b9

Observation a5f9e9fc-c6b3-4d6c-8eab-ef2dc815bdc0 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

GPR: Empowering Generation with Graph-Pretrained Retriever Representation Learning with Contrastive Predictive Coding

Reference 2018

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source=pdf_text observed=2026-08-07T12:13:01.057421Z digest=sha256:0c4ffc37756100ca24ec13f95c8724c3607ffa479b70e48dd8c9542cb4206961

Observation 78550a01-e6ba-4c91-9dc9-8d4f5eb31c9d · outbound

This paper cites an unresolved cited work.

GPR: Empowering Generation with Graph-Pretrained Retriever Unresolved cited work

Reference 2019

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:12:59.634037Z digest=sha256:f7050b8a9c2fd1b69a205c34e87de6afd818f18ed3757bd2a5183377b3f7bbe5

Observation c6f64b5d-a87f-4889-80bd-274ffbd07eb3 · outbound

This paper cites an unresolved cited work.

GPR: Empowering Generation with Graph-Pretrained Retriever Unresolved cited work

Reference 2020

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T12:13:02.099792Z digest=sha256:74a9f59cd74682685ac630cfa432061b3301e902deb8f91b48728ba5ff7d8ae3

Observation 8672aa27-eee8-456e-8062-6f3a5b554865 · outbound

This paper cites GPT-4 Technical Report.

GPR: Empowering Generation with Graph-Pretrained Retriever GPT-4 Technical Report

Reference 2023

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source=pdf_text observed=2026-08-07T12:12:59.335089Z digest=sha256:202cb79b84d6a71003ee0b14ce97d4f186c19fc78e1f3985dbf564655fe5dfdf

Observation b2ea06af-eb16-4508-953e-bf15039fe5bf · outbound

This paper cites The Llama 3 Herd of Models.

GPR: Empowering Generation with Graph-Pretrained Retriever The Llama 3 Herd of Models

Reference 2024

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:59.971190Z digest=sha256:e9931deeed2c5e5b0ef4acf9560772463125799f3defd7411e0572668f1c7b84

Observation 3b5bc858-fa54-460c-b0cc-90eb8dd418a0 · outbound

This paper cites arXiv preprint arXiv:2501.13958.

GPR: Empowering Generation with Graph-Pretrained Retriever arXiv preprint arXiv:2501.13958

Reference 2025

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:13:01.822375Z digest=sha256:3c9de8aadac94d700555464d4af03438f685b09795c393a545c547ac365a4972

Pith citing papers

No inbound Pith citation observations are available.