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Paper Citation Record · LEDGER

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG

As of 9 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 1 inbound Pith citation observation for arXiv:2506.06331.

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

pith.paper-citation-record.v1
2506.06331 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:09:56.622230Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T05:26:34.543601Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:09:51.256164Z

Reference resolution

42 of 42 outbound references displayed

  • verified exact1
  • verified fuzzy2
  • unresolved39
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation eea22e00-5590-4e04-9c8a-5e8652d459d3 · outbound

This paper cites Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models

Reference 1

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no resolver link, observed 2026-08-07T12:09:52.100887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:52.100887Z digest=sha256:99502dce76af03c8140cbe8abc9bdb4374d1eecb1094e381af33db164e804968

Observation 8102f06b-cf39-4779-a504-804da4acc9ee · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 2

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no resolver link, observed 2026-08-07T12:09:52.598430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:52.598430Z digest=sha256:62bf476bd115995319cd7887db13ebd949c0bb7b219261c71b8ce4fc2ac31b11

Observation 365d8262-1e73-4516-babf-489ea127bf12 · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 3

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raw_fallback, observed 2026-08-07T12:09:59.392161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:09:53.057555Z digest=sha256:19599ab929936dd4fbf3869a00e8be962ef8bcaecf94d93e462409c214bb1bef

Observation 66662935-65a0-46e2-b209-56480bc9acf4 · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 4

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raw_fallback, observed 2026-08-07T12:09:59.139215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:09:53.186420Z digest=sha256:e77f93f5596c5e3c2411e66c151c224dd761ca0898b258686d09b74dea76fdd2

Observation c1933a8e-b3d0-405c-be0a-094c8a48f047 · outbound

This paper cites Can Large Language Models Be an Alternative to Human Evaluations?.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Can Large Language Models Be an Alternative to Human Evaluations?

Reference 5

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no resolver link, observed 2026-08-07T12:09:53.297574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:53.297574Z digest=sha256:6d32f5cac6b3868db2d05761a6677f1fce7c3cdfa442e093aec29cf16b8bdf81

Observation e9fe1194-b5bd-4086-8c6f-3c7e9ecad78f · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:09:58.868469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:09:53.412372Z digest=sha256:7f131ed0017c4ca822067711766ac9b37411e97f09dd657d3024723e268b7f62

Observation 576e6dd6-4814-4853-86a6-26b67d289808 · outbound

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

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG From Local to Global: A Graph RAG Approach to Query-Focused Summarization

Reference 7

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no resolver link, observed 2026-08-07T12:09:53.499645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:53.499645Z digest=sha256:c37a7d092a2e88ab26903a659d9fccb94bfbf8181cae97d3e5bbdf7e08684d2b

Observation bacdf5c6-f730-4c27-b261-136adc0a3707 · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 8

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raw_fallback, observed 2026-08-07T12:09:58.558963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:09:53.635766Z digest=sha256:c26613875fb2f45b9d388f14c65b3892f724df966445fd1a4d3d05e3a7fe9fb9

Observation 40ac6b89-16a7-4830-8dcb-095484f6d103 · outbound

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

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 9

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no resolver link, observed 2026-08-07T12:09:53.739243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:53.739243Z digest=sha256:865729df5816ac11e18603163178ec36cf27e7a16f3901ed29e91874589f145c

Observation ef4b353e-f01b-43a1-a563-5fb1db6a1c8c · outbound

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

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG LightRAG: Simple and Fast Retrieval-Augmented Generation

Reference 10

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no resolver link, observed 2026-08-07T12:09:53.847820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:53.847820Z digest=sha256:07714b5aa583820bc84cdbd2f231edb4125c20e7a85d1921341481be67e78c41

Observation 5022996f-82a5-48bb-989e-3efaa01cb132 · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 12

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no resolver link, observed 2026-08-07T12:09:54.081767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:54.081767Z digest=sha256:b57f8f41de53fe51d5c18f7e144dab6123ec2551dcfab7561c09d6234f0c15bd

Observation 7b84d0c7-a2f8-4e13-981b-ec0c425159ad · outbound

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

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Retrieval-Augmented Generation with Graphs (GraphRAG)

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:54.253352Z digest=sha256:f0f00bfe6ee96a21bd724ae0ae190404e811554364c8927b72199cf24a58dc71

Observation 5797fb3d-b8ad-4387-be65-a15f9c9b120c · outbound

This paper cites Authorea Preprints (2023).

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Authorea Preprints (2023)

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:09:57.875967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:09:54.159781Z digest=sha256:fa5500247867d1f359f78edd16302defbb06351afbb626e0107f623bc2a27896

Observation b4e36222-f3c2-489f-8616-4934665ef03e · outbound

This paper cites G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering

Reference 15

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no resolver link, observed 2026-08-07T12:09:54.408861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:54.408861Z digest=sha256:8a03ae0b66063ba111ff3beed3e5c19f864e05855c23966f788ae42c03da16a5

Observation 4077b428-7e9c-4a91-8789-a892b334e31d · outbound

This paper cites RAG-QA Arena: Evaluating Domain Robustness for Long-form Retrieval Augmented Question Answering.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG RAG-QA Arena: Evaluating Domain Robustness for Long-form Retrieval Augmented Question Answering

Reference 16

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verified exact
local_arxiv, observed 2026-08-07T12:09:57.072728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:09:54.330786Z digest=sha256:4641e2326194055755aaa1988f56bcc52ce38b12fde00fba472339d386e6d22a

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

This paper cites RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing.

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

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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:c9f0acf8b929a1c126ea7087d12d734b8ae5dd13a2ee0826db184f65f0af6500

Observation b0469d32-a96b-4645-8acf-2e26a84cd73c · outbound

This paper cites GRAG: Graph Retrieval-Augmented Generation.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG GRAG: Graph Retrieval-Augmented Generation

Reference 18

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no resolver link, observed 2026-08-07T12:09:54.491432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:54.491432Z digest=sha256:392166b1528dce6cb237c14fa629da295b39bd04ee353ad8eaf91e24d5be2e45

Observation 25bd15e8-66c3-4d74-853d-9c414bb2aeed · outbound

This paper cites Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:54.842400Z digest=sha256:d462541a865fd47a8e7b451ce10f577d78a556d7aae0b9286c087de04506e6f2

Observation c41f0bbe-0aa2-406b-90b7-9d8c803ca645 · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:54.647186Z digest=sha256:c265593c4393e62d5a8d3e7cc3c933540ee87bc43fb860518901422645586628

Observation 1a70f652-00cd-4424-83d9-f4e5b3fc06f4 · outbound

This paper cites A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:54.750993Z digest=sha256:eedea687a20745d8edeccd425c32d2ff9b5a65692d305e29e3ac5a13baabf443

Observation cdbd5fc2-b153-4c5b-ab91-9e9e57462027 · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 22

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no resolver link, observed 2026-08-07T12:09:55.110824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:55.110824Z digest=sha256:fd29a08677b1e38bd8920ee4d8e0c7c8cfa3dd6f0fd96eb3609237be9eb381ba

Observation 9ea3cf4e-ab13-499b-9030-1e602fe379cd · outbound

This paper cites Large Language Models Are State-of-the-Art Evaluators of Translation Quality.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Large Language Models Are State-of-the-Art Evaluators of Translation Quality

Reference 23

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no resolver link, observed 2026-08-07T12:09:54.928802Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:54.928802Z digest=sha256:cd585693c0bbcf2f9104fca47b0ff6403cb21eab08cfce0ba68a990238fbbc2a

Observation 7f8c52eb-bf3d-45ca-a47d-73e3c1a04a6a · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:09:55.023914Z digest=sha256:38939ce94e610b51f71c1c0f66493096d3ae54be330f9e5eae3c0dd79343e765

Observation 3c00f0c1-f306-4aaf-820b-d7eddf6346fb · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 25

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raw_fallback, observed 2026-08-07T12:09:57.502125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:09:55.422965Z digest=sha256:4faf9aa373bd7ea03ab1fed465e6016f1bc55baff2f254d92e42a0c4e8b5eaab

Observation 4068be9d-418f-4d2d-8c04-8c37d0b311d4 · outbound

This paper cites LLM-Eval: Unified Multi-Dimensional Automatic Evaluation for Open-Domain Conversations with Large Language Models.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG LLM-Eval: Unified Multi-Dimensional Automatic Evaluation for Open-Domain Conversations with Large Language Models

Reference 26

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:55.224300Z digest=sha256:de26e54361c3f5e1337a694e9899e905edd4a517638be9edc423b0ef8e9b6089

Observation 2977eafd-1c8a-471f-a688-5600855e305c · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 27

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raw_fallback, observed 2026-08-07T12:09:57.621584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:09:55.330801Z digest=sha256:88b7c29803c98b48ca4d0ee9fea42bcecc49808ac1f86852e13c0917545b78a6

Observation 46360ffe-3d27-4ca9-a0c2-c94f37ef7ebd · outbound

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

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models

Reference 28

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no resolver link, observed 2026-08-07T12:09:55.684978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:55.684978Z digest=sha256:cd8b3cc4ba7aa9a17de1c67fd48c23defc10467edc7016e9db223b0b6c0602a8

Observation 538c6878-e27e-4034-b44c-3e1d7aa99845 · outbound

This paper cites MemoRAG: Boosting Long Context Processing with Global Memory-Enhanced Retrieval Augmentation.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG MemoRAG: Boosting Long Context Processing with Global Memory-Enhanced Retrieval Augmentation

Reference 29

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source=pdf_text observed=2026-08-07T12:09:55.510944Z digest=sha256:23263563778223ebe5eff22cdc2afa48a5e01f16a2b82201173d3f05649cd7cf

Observation 85baa367-4b1b-4b95-8d2b-d53fdfe2ce98 · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 30

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no resolver link, observed 2026-08-07T12:09:55.597316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:55.597316Z digest=sha256:834776dda54535655ec49863075f8baf81706aca1dc87edf1669a7b50252b459

Observation 136bc01d-9ad6-49d4-a1d2-324c67312e8b · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 31

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no resolver link, observed 2026-08-07T12:09:55.934929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:55.934929Z digest=sha256:5c3279793e7ad4b69ce3a0d1545d1094dddf94aecbf09bbac7c8578142183caf

Observation dfb6a41e-ca9b-4232-8f12-83f7757c1b8e · outbound

This paper cites Are Expert-Level Language Models Expert-Level Annotators?.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Are Expert-Level Language Models Expert-Level Annotators?

Reference 32

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no resolver link, observed 2026-08-07T12:09:55.773665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:55.773665Z digest=sha256:776515395341b62b145cd01618e7cc587e9b78b35baae34fa213c89841a56974

Observation a684123e-71bb-45fa-ab66-282c67d0807a · outbound

This paper cites Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity

Reference 33

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no resolver link, observed 2026-08-07T12:09:55.855707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:55.855707Z digest=sha256:a52814ec4f7e8c1c3131c24f5751764c7b39327eca7275ff3faea635498ceb94

Observation 2b5071bc-5af3-41d6-81dd-0ede1ada0644 · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 34

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:56.265393Z digest=sha256:06a12cd4865ff347448547a97b88ac544691a24f236ff843a837ff27e76496da

Observation 1dba7e0e-07fa-46df-8262-9d80202ef284 · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 35

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unresolved
raw_fallback, observed 2026-08-07T12:09:57.285781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:09:56.422009Z digest=sha256:3616c05e14ebd8a3ef2f56cf13b8c2563af0d2b20feab52a05eb94559515b0e9

Observation d672dc24-22ef-43e2-9887-d6a2539cfab6 · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 36

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no resolver link, observed 2026-08-07T12:09:56.067106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:56.067106Z digest=sha256:e59b2fd666fd1bd4e05cd8d4ed9ef495b23be6218ec83e8bab7cb385fa569bcc

Observation b3ad1123-e0ae-4469-afbb-e6e9d7b3bac2 · outbound

This paper cites an unresolved cited work.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Unresolved cited work

Reference 37

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raw_fallback, observed 2026-08-07T12:09:57.412074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:09:56.172292Z digest=sha256:982e7b31dd5161bd83ca48e7ad3230c7b6995a187ecc45df55888bc7cdd5c915

Observation fed30cbf-afac-42d5-9cbd-4ed86d6b6b99 · outbound

This paper cites illusion.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG illusion

Reference 38

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no resolver link, observed 2026-08-07T12:09:56.622230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:56.622230Z digest=sha256:72b4c23d8fbe1bb25fa2d5e81a579d2017841a5f4e9b5620f454400b6f3b30c9

Observation 4eb8cbae-bb8b-4342-8bf2-c4f17e618159 · outbound

This paper cites Efficient Streaming Language Models with Attention Sinks.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Efficient Streaming Language Models with Attention Sinks

Reference 39

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unresolved
no resolver link, observed 2026-08-07T12:09:56.358837Z

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source=pdf_text observed=2026-08-07T12:09:56.358837Z digest=sha256:9e751fc94e93cdd90fadaea65d3420e37dac1de32da8313ed38d70295e845eda

Observation 3aa867e1-1afd-4640-a17f-4c046d537394 · outbound

This paper cites Graph of Records: Boosting Retrieval Augmented Generation for Long-context Summarization with Graphs.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Graph of Records: Boosting Retrieval Augmented Generation for Long-context Summarization with Graphs

Reference 41

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unresolved
no resolver link, observed 2026-08-07T12:09:56.478822Z

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source=pdf_text observed=2026-08-07T12:09:56.478822Z digest=sha256:e060570db3c72e90af0f00f335a589508b5d96304d62163c37f09a51d0b330f7

Observation 72d2e07f-2ef0-43ff-906d-29c59cd62661 · outbound

This paper cites Trustworthiness in Retrieval-Augmented Generation Systems: A Survey.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Trustworthiness in Retrieval-Augmented Generation Systems: A Survey

Reference 42

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unresolved
no resolver link, observed 2026-08-07T12:09:56.534287Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T12:09:56.534287Z digest=sha256:6befc74ada4d3526b42e8773adc658dedd9522cc5cbadb5c3dd8d46b9cfd5df1

Observation 85ee2d71-2136-4a9b-9e10-688bdda89f09 · outbound

This paper cites Authorea Preprints (2023).

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Authorea Preprints (2023)

Reference 2023

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verified fuzzy
raw_fallback, observed 2026-08-07T12:09:58.223435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:09:54.004066Z digest=sha256:e99ea5cc676a86204817ce14b030c4077032858e6386ed2bc142097a7ae4c7d4

Observation 53070168-532d-41d6-9a2d-7049534bf9d1 · outbound

This paper cites Evaluating Quality of Answers for Retrieval-Augmented Generation: A Strong LLM Is All You Need.

How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG Evaluating Quality of Answers for Retrieval-Augmented Generation: A Strong LLM Is All You Need

Reference 2024

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unresolved
no resolver link, observed 2026-08-07T12:09:55.988580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:55.988580Z digest=sha256:4ad51dc2a95bb954240f6a1a25207945e4463945b53db74b68f3af12e1cb15ea

Pith citing papers

Observation 9e5504e2-13b3-4f8d-af69-e27736bfca6c · inbound

Temporal Validity in Retrieval Memory: Eliminating Stale-Fact Errors for AI Agents over Evolving Knowledge cites this paper.

Temporal Validity in Retrieval Memory: Eliminating Stale-Fact Errors for AI Agents over Evolving Knowledge How Significant Are the Real Performance Gains? An Unbiased Evaluation Framework for GraphRAG

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-07-04T13:09:51.257611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-26T05:26:34.543601Z digest=sha256:f63f494d03bf70568a7303cdb03dd09b7ff59e433267cb217036eb31878f33fe