Paper Citation Record · LEDGER

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval

As of 8 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2607.20506.

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

pith.paper-citation-record.v1
2607.20506 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T08:58:44.086193Z

measured 26 of 26 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

26 of 26 outbound references displayed

verified exact0
verified fuzzy0
unresolved26
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation da60f3fd-82ff-4ece-b8dd-e7e846cca096 · outbound

This paper cites Introducing contextual retrieval, 2024.https://www.anthropic.com/ engineering/contextual-retrieval.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval Introducing contextual retrieval, 2024.https://www.anthropic.com/ engineering/contextual-retrieval

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:41.304958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7c616b4-24a3-47cd-84e2-a50174ddda98 · outbound

This paper cites Pathrag: Pruning graph-based retrieval aug- mented generation with relational paths, 2025.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval Pathrag: Pruning graph-based retrieval aug- mented generation with relational paths, 2025

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:41.425173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0d8d8f7-891e-42b0-8c32-885a5f9e2228 · outbound

This paper cites Universal self-consistency for large language models.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval Universal self-consistency for large language models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:41.537975Z

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Unavailable: canonical work link unavailable.

Observation ab8ab678-2b17-4e45-9254-e0d78200f23b · outbound

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

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval From Local to Global: A Graph RAG Approach to Query-Focused Summarization

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:41.694240Z

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Unavailable: canonical work link unavailable.

Observation f1edcd80-700b-4bf9-a495-589506d82d38 · outbound

This paper cites RAGAs: Automated evaluation of re- trieval augmented generation.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval RAGAs: Automated evaluation of re- trieval augmented generation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:41.791670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc70b2a4-aa09-47dc-8c02-7dc4018913db · outbound

This paper cites Hyper-rag: Combating llm hallucinations using hypergraph-driven retrieval-augmented genera- tion, 2025.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval Hyper-rag: Combating llm hallucinations using hypergraph-driven retrieval-augmented genera- tion, 2025

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:41.877702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 161b2ae1-4252-413a-aa35-0ba01aab4f74 · outbound

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

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval LightRAG: Simple and Fast Retrieval-Augmented Generation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:41.941607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b9b3ff8-7825-44f9-bceb-2194e88b807b · outbound

This paper cites From RAG to memory: Non- parametric continual learning for large language mo- dels.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval From RAG to memory: Non- parametric continual learning for large language mo- dels

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:42.005394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69251d9f-71b2-4696-a090-82fcd421aed9 · outbound

This paper cites G-retriever: Retrieval-augmented gene- ration for textual graph understanding and question answering.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval G-retriever: Retrieval-augmented gene- ration for textual graph understanding and question answering

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:42.045180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e3993f3-471d-4956-9a71-28e3f9215fe7 · outbound

This paper cites GRAG: Graph retrieval- augmented generation.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval GRAG: Graph retrieval- augmented generation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:42.149271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ad9127f-e338-4062-9312-4ca32480f609 · outbound

This paper cites Ket- rag: A cost-efficient multi-granular indexing frame- work for graph-rag.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval Ket- rag: A cost-efficient multi-granular indexing frame- work for graph-rag

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:42.254250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0374c47a-c16a-44c7-b2d0-9421879faeee · outbound

This paper cites Retrieval- augmented generation for knowledge-intensive nlp tasks.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval Retrieval- augmented generation for knowledge-intensive nlp tasks

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:42.314188Z

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Unavailable: canonical work link unavailable.

Observation b495719c-783c-45ca-911a-d83c4f8c3c20 · outbound

This paper cites Kag: Boosting llms in professional do- mains via knowledge augmented generation.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval Kag: Boosting llms in professional do- mains via knowledge augmented generation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:42.388740Z

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Unavailable: canonical work link unavailable.

Observation 26ef39d6-32e3-44e2-b37b-80fc216059ef · outbound

This paper cites Hypergraphrag: Retrieval-augmented genera- tion via hypergraph-structured knowledge representa- tion, 2025.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval Hypergraphrag: Retrieval-augmented genera- tion via hypergraph-structured knowledge representa- tion, 2025

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:42.488320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 629bae7c-2f76-4848-9fa7-da408ff1b7a9 · outbound

This paper cites Creating knowledge graphs from unstructured data.https://neo4j.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval Creating knowledge graphs from unstructured data.https://neo4j

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:42.648159Z

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Observation b59db531-16e1-4e12-a0f6-4dcb096afe17 · outbound

This paper cites LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:42.760654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14de4922-65e5-4fc7-85f4-61870c9eb355 · outbound

This paper cites Memorag: Boosting long context processing with glo- bal memory-enhanced retrieval augmentation.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval Memorag: Boosting long context processing with glo- bal memory-enhanced retrieval augmentation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:42.901743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 074c95b1-0f28-4ccd-916a-fccbe1ef4053 · outbound

This paper cites Le, Ed H.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval Le, Ed H

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:43.058776Z

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Observation ff3e9096-c1e2-4a96-a2b1-7dac37c5a8d6 · outbound

This paper cites Large language models for gene- rative information extraction: a survey.Frontiers of Computer Science, 18, 2024.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval Large language models for gene- rative information extraction: a survey.Frontiers of Computer Science, 18, 2024

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:43.160614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ecee93c7-2c8a-470d-8e92-6a80b9d6ae63 · outbound

This paper cites Recent advances in hypergraph neural networks.Journal of the Opera- tions Research Society of China, 2025.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval Recent advances in hypergraph neural networks.Journal of the Opera- tions Research Society of China, 2025

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:43.329081Z

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Unavailable: canonical work link unavailable.

Observation 3e81255a-8bc1-47e0-aa46-7d488fbbb95e · outbound

This paper cites Proh: Dynamic plan- ning and reasoning over knowledge hypergraphs for retrieval-augmented generation, 2026.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval Proh: Dynamic plan- ning and reasoning over knowledge hypergraphs for retrieval-augmented generation, 2026

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:43.468737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f7b19e0-b8f2-4142-bf53-698e510e78e2 · outbound

This paper cites Graph-based ap- proaches and functionalities in retrieval-augmented generation: A comprehensive survey.ACM Comput.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval Graph-based ap- proaches and functionalities in retrieval-augmented generation: A comprehensive survey.ACM Comput

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:43.544342Z

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Unavailable: canonical work link unavailable.

Observation 394dd4a8-64f2-43e0-95c6-9acc5907f3dc · outbound

This paper cites •Each run must complete all steps as a separate, uninfluenced process.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval •Each run must complete all steps as a separate, uninfluenced process

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:43.710504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55e84344-7814-4279-abf4-ef7adb58a102 · outbound

This paper cites •If multiple segments describe the same concept/relationship, combine them into ONE segment with the highest comple- teness score.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval •If multiple segments describe the same concept/relationship, combine them into ONE segment with the highest comple- teness score

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:43.858536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51bbe655-0982-4fe7-a119-8e063d7c5167 · outbound

This paper cites For each knowledge segment, extract the following information: •knowledge_segment: Extract 1–3 consecutive sentences EXACTLY as they appear in the source text.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval For each knowledge segment, extract the following information: •knowledge_segment: Extract 1–3 consecutive sentences EXACTLY as they appear in the source text

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:43.970099Z

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Observation 27c387d3-4a58-4ce7-8948-8533074d9066 · outbound

This paper cites How does Vadassy’s plan to trap the spy ultimately fail?.

Optimizing Hypergraph-Based RAG: Toward Better Fact Extraction and Chunk Retrieval How does Vadassy’s plan to trap the spy ultimately fail?

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T08:58:44.086193Z

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Pith citing papers

No inbound Pith citation observations are available.