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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:b054d812205a1228b0758469115428034be6b4d8749b670f9309c080a1b3606c

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=sha256:04968e49db6134320889a78fa197ee028c05ee8ccefc119d9bef19a20632cd43

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

Resolution
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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:b3a2068dcadf417d15583eca287e379a0f540cc3a287549a05e38905c6062503

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=sha256:0834d5a207288aa4dcea92d2f905af6361528ca28a2c17bb49888aae7b939689

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=sha256:490a7b030e28e4668df0df6ff43cd974d1d4fdc32818cb43b7b4af0da7eb6508

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

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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:ab25c3da189f7d937a5f026791e2551dde7c5a6fea2a6804485f4679a274ec4f

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=sha256:24130e0d50ddaa3572bd1d11b69274909f7a2c6050a7926ce7e525e08356c310

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=sha256:781bd52cb261ba070bb4d42ba39aee1ac8d86e7c4e0f3fd5bc490ba6e416f369

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:fcd770abf4faf399427526b01e174d0c35ad675def23441be5ad2f9a6f79697b

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=sha256:2fcd778492138402fdcd25cad8a457800b43cb8fda03deaa3874154ad4a80d79

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=sha256:1f7b78d90da9743bb30b52b437bdb4430e7d4674a745ecfc346b2cede6e34d47

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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no resolver link, observed 2026-08-07T12:09:54.253352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:54.253352Z digest=sha256:1ae52e2ee4f165b6865f2cce2e9ddf3d3b6c4b907792c736397ccfa6e84ed0ad

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=sha256:143f62abb3b903b853048ba0f97a29ad1e116cb90788fcc40d53472154752e11

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:b14acd8296406b205b321e2d923d62be3bde17afea34950372741827e284a88e

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=sha256:8d1608447daee3c32a2fe3206ebe23cca191c318b2b85afb1b38b5510a78c351

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=sha256:0e46779b9d7679e6d6f23ea4117948c596b9165c445de3dc5239c102cc896d0c

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=sha256:1f3289e62d188751728d0fe06ad1ba402ce3af22f89e7db806bea6d2b4062556

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:f1d51f2a1a0a0a296d3457c7373780841d0187c9600b580b32e4856fdc6c8b1d

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:fe70667ed663b0e455431e45ef96790f3ba3590ebaf20c285ab89eeda817e3af

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:fc58b3fa7829b3856e1380fec426f1588891009d44ff5f416f0c4ca91dcdcd1d

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:55.110824Z digest=sha256:fd9dbc4ed1b3b8b0555729b2c2dd93c978fa2ac034d44c75fdbd42efe5164bba

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:54.928802Z digest=sha256:825f7218ff8eb7f28c29663284ef79154c9ecb0f14038165b9bcd24de968ffd4

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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raw_fallback, observed 2026-08-07T12:09:57.731347Z

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=sha256:84b28ce394d8e8faa36854cd6729c8005d29076d64c582e35949df4a7761d998

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:a13132ace2db54e7b210eb25c41cfcb8b9561c2d9e379142f0c28b98af703230

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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source=pdf_text observed=2026-08-07T12:09:55.224300Z digest=sha256:0f44ce8aaabc612258d43d118dbbd7dcbd553442ae9091b1d4330cdf9a0b9579

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.

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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=sha256:4caf4ee6b0b97a6d62ab84d1520531d1e6f7cba2c8e0294bdca2bfbccde4ccb2

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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no resolver link, observed 2026-08-07T12:09:55.510944Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:55.510944Z digest=sha256:3759f45f0aae2e6cd0874917519206da6b64b59da1827a3ba2e7d7a6d4264009

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=sha256:4b1fc900032869ec85a9061358668af7eebb82429947c0cfc723a093d28ca095

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=sha256:39e4bf1cf236a9f567b4e24b2be7a1f3df48a0cef25cd32904619208d93a529b

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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:55.773665Z digest=sha256:625816cc6d18c4211084d91fd1d97fa0f1b78b23b9a670334952a885b54f3467

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:c9d4cbee4685541cd6a15b43bd044d433c753c40a8246481f0b8aa735537c060

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=sha256:4a9cac21fca7b269519080454fd0065d6e9bf7344fb921446841a8bc35acb584

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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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:a2778cc9579667101fab3b12435381b36da9f02c08d5d9686b66016e03433e08

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:bccf74d45367e7087dbfeebe9f6d12661b27bf8650b6199146623b7eb7c2d603

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=sha256:4a47116f23ca1c832cb63ba591b11d1a91dc23363a00eb88916c7933711ff963

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.

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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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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

Source-reported events for the cited work

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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

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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

Resolution
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.

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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

Resolution
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:ab04c8d7adcc8c4fc20d95739704526bc9f9a790ffb015362b49d899251d596f

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=sha256:81f7c2146a46b03bad57f04ac580aaefbf211901fe78a294ded553417c2095ab