Paper Citation Record · LEDGER

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation

As of 7 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 14 inbound Pith citation observations for arXiv:2506.02404.

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

pith.paper-citation-record.v1
2506.02404 v3

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:28:32.600962Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:22:06.395124Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T08:57:47.484346Z

Reference resolution

23 of 23 outbound references displayed

verified exact0
verified fuzzy19
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3d411069-1e05-4739-a072-7205cff61f81 · outbound

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

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation Retrieval-augmented generation for knowledge-intensive nlp tasks,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:35.940486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 306387fa-5783-42c0-af83-269cfc941ce9 · outbound

This paper cites Retrieval-augmented generation for large language models: A survey,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation Retrieval-augmented generation for large language models: A survey,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T11:28:30.781571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c907305-a29d-4f37-860c-ba63deb2f807 · outbound

This paper cites A survey of graph retrieval-augmented generation for customized large language models,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation A survey of graph retrieval-augmented generation for customized large language models,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:35.730520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 64e1ec78-615d-4722-ba9b-38d437f1493f · outbound

This paper cites Hierarchy-aware multi-hop question answering over knowledge graphs,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation Hierarchy-aware multi-hop question answering over knowledge graphs,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:35.541240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 92444fd8-1103-4f8a-90cf-4f5d3cffd63c · outbound

This paper cites From local to global: A graph rag approach to query-focused summarization,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation From local to global: A graph rag approach to query-focused summarization,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:35.386219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 174de229-bd60-4efe-b8b6-419ceb5cf069 · outbound

This paper cites Graph retrieval-augmented generation: A survey,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation Graph retrieval-augmented generation: A survey,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:35.229822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fbdf48a8-d9bb-4774-b129-54d2f549cd09 · outbound

This paper cites In-depth analysis of graph-based rag in a unified framework,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation In-depth analysis of graph-based rag in a unified framework,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:35.074495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ef1cec0b-efc9-43e9-96e7-794398b40635 · outbound

This paper cites RAPTOR: Recursive ab- stractive processing for tree-organized retrieval,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation RAPTOR: Recursive ab- stractive processing for tree-organized retrieval,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:34.870267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7aca14c8-032f-4511-b22c-81157e8bd36c · outbound

This paper cites Gfm-rag: Graph foundation model for retrieval augmented generation,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation Gfm-rag: Graph foundation model for retrieval augmented generation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:34.676651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7f993d90-f4f2-4346-b224-fc55158f385b · outbound

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

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation G-retriever: Retrieval-augmented generation for textual graph understanding and question answering,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:34.538294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9f6eec37-76f4-42e1-b155-5e5c2e5e0b89 · outbound

This paper cites DALK: Dynamic co-augmentation of LLMs and KG to answer Alzheimer‘s disease questions with scientific literature,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation DALK: Dynamic co-augmentation of LLMs and KG to answer Alzheimer‘s disease questions with scientific literature,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:34.332529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 32be7661-c7e8-4b2c-8f45-37272611f2dc · outbound

This paper cites Think-on-graph: Deep and responsible reasoning of large language model on knowledge graph,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation Think-on-graph: Deep and responsible reasoning of large language model on knowledge graph,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T11:28:31.700246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7eb78438-8188-4207-9f47-1aaa44e48fb1 · outbound

This paper cites HotpotQA: A dataset for diverse, explainable multi-hop question answering,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation HotpotQA: A dataset for diverse, explainable multi-hop question answering,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:34.112158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 57a2180f-e733-4c02-b3a3-04216312e50b · outbound

This paper cites Constructing a multi-hop QA dataset for comprehensive evaluation of reasoning steps,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation Constructing a multi-hop QA dataset for comprehensive evaluation of reasoning steps,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:33.937710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 662458ae-9e1e-41bc-a3d2-2c38daf3af35 · outbound

This paper cites Musique: Multihop questions via single-hop question composition,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation Musique: Multihop questions via single-hop question composition,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T11:28:32.014451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3eb43892-11f5-4721-afa5-1426cc755ba7 · outbound

This paper cites Lightrag: Simple and fast retrieval-augmented generation,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation Lightrag: Simple and fast retrieval-augmented generation,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T11:28:32.097796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba3da39e-e036-45a4-ae1b-314d0bf3e0cc · outbound

This paper cites Hipporag: Neurobiologically inspired long-term memory for large language models,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation Hipporag: Neurobiologically inspired long-term memory for large language models,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:33.736152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f303a7da-e2ae-4408-aed5-ce6441e84e84 · outbound

This paper cites Knowledge graph prompting for multi- document question answering,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation Knowledge graph prompting for multi- document question answering,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:33.591061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 67762bc2-ceb2-4bec-9e94-3fc06a20156c · outbound

This paper cites QuALITY: Question answering with long input texts, yes!,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation QuALITY: Question answering with long input texts, yes!,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:33.415773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 795faa38-ed50-44ea-9567-ab2d635c9944 · outbound

This paper cites When not to trust language models: Investigating effectiveness of parametric and non-parametric memories,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation When not to trust language models: Investigating effectiveness of parametric and non-parametric memories,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:33.223657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fbdbe92a-4e62-4d93-8c63-ea45218b1d16 · outbound

This paper cites Layoutlmv3: Pre-training for document ai with unified text and image masking,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation Layoutlmv3: Pre-training for document ai with unified text and image masking,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:33.003776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e4d99ab6-ab13-47db-9520-f86e0e8e172e · outbound

This paper cites Yolov10: Real-time end-to-end object detection,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation Yolov10: Real-time end-to-end object detection,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:32.866162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 53d05013-ed35-4f05-87d6-b47c0ff92926 · outbound

This paper cites Mineru: An open-source solution for precise document content extraction,.

GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation Mineru: An open-source solution for precise document content extraction,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:28:32.703523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

Observation 441d5b35-e796-4ceb-af3a-95885345b94b · inbound

Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning cites this paper.

Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation

Reference 970

Resolution: unresolved; no resolver link, observed 2026-08-06T12:22:06.395124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71a9dbba-db97-4a04-9040-74f6325c2e3a · inbound

Youtu-GraphRAG: Vertically Unified Agents for Graph Retrieval-Augmented Complex Reasoning cites this paper.

Youtu-GraphRAG: Vertically Unified Agents for Graph Retrieval-Augmented Complex Reasoning GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T15:29:57.204214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a7b0ba7-b62d-46ed-a3ab-d0234eb73b79 · inbound

G-reasoner: Foundation Models for Unified Reasoning over Graph-structured Knowledge cites this paper.

G-reasoner: Foundation Models for Unified Reasoning over Graph-structured Knowledge GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:26:24.986243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8fe4fcd3-1876-40b0-83a4-31ca96a5f30b · inbound

LogicPoison: Logical Attacks on Graph Retrieval-Augmented Generation cites this paper.

LogicPoison: Logical Attacks on Graph Retrieval-Augmented Generation GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T19:48:11.500189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 36677a63-83e6-444c-a141-36a447f0de8d · inbound

Hierarchical Abstract Tree for Cross-Document Retrieval-Augmented Generation cites this paper.

Hierarchical Abstract Tree for Cross-Document Retrieval-Augmented Generation GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:31:06.432336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 609815de-5cd7-4034-9bdd-cb9d9c510c0b · inbound

MoG: Mixture of Experts for Graph-based Retrieval-Augmented Generation cites this paper.

MoG: Mixture of Experts for Graph-based Retrieval-Augmented Generation GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-07-01T19:36:08.119324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 854cd146-abfc-4d04-88c1-6377692d7e9a · inbound

Reducing Hallucinations in Complex Question Answering using Simple Graph-based Retrieval-Augmented Generation (long version) cites this paper.

Reducing Hallucinations in Complex Question Answering using Simple Graph-based Retrieval-Augmented Generation (long version) GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-07-02T13:26:59.385504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 08a5fdd8-13b6-4fb1-9964-df76ffbbf9a9 · inbound

Reducing Hallucinations in Complex Question Answering using Simple Graph-based Retrieval-Augmented Generation (long version) cites this paper.

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-02T12:21:44.230765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 365d7ee3-58dc-48e4-a582-9e5f09619bf3 · inbound

GraphInfer-Bench: Benchmarking LLM's Inference Capability on Graphs cites this paper.

GraphInfer-Bench: Benchmarking LLM's Inference Capability on Graphs GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-07-03T08:57:47.485990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 28d0da39-96b0-4197-bc6e-31e013bed273 · inbound

Efficient Retrieval-Augmented Generation via Token Co-occurrence Graphs cites this paper.

Efficient Retrieval-Augmented Generation via Token Co-occurrence Graphs GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-06-30T06:14:18.909263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0a4a0624-9f20-4849-bdc7-736a8a9892a5 · inbound

HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering cites this paper.

HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-02T11:36:07.959250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed8893ce-e763-4ecb-ac4a-f2324d47d817 · inbound

Reason Before You Retrieve: Agentic Planning for Multi-modal RAG cites this paper.

Reason Before You Retrieve: Agentic Planning for Multi-modal RAG GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation

Reference 168

Resolution: unresolved; no resolver link, observed 2026-08-02T10:20:56.322698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e229604-63b9-44f2-b83a-281b864a11df · inbound

HiEviDR-Bench: A Benchmark for Hierarchical Evidence Aggregation in Deep Research cites this paper.

HiEviDR-Bench: A Benchmark for Hierarchical Evidence Aggregation in Deep Research GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation

Reference 34

Resolution: unresolved; no resolver link, observed 2026-07-31T00:05:16.886205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41fc6741-48ee-4534-bc47-cc74b0fd1138 · inbound

GLM-RAG: Graph Language Models for Graph-Based Retrieval-Augmented Generation cites this paper.

GLM-RAG: Graph Language Models for Graph-Based Retrieval-Augmented Generation GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation

Reference 49

Resolution: unresolved; no resolver link, observed 2026-07-31T08:45:17.046736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.