Paper Citation Record · LEDGER

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation

As of 19 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 2 inbound Pith citation observations for arXiv:2505.17058.

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

pith.paper-citation-record.v1
2505.17058 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:49:06.257472Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:21:03.136823Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T17:20:00.992143Z

Reference resolution

32 of 32 outbound references displayed

verified exact0
verified fuzzy24
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 14221956-3871-4a74-b79a-32c1a5071a78 · outbound

This paper cites an unresolved cited work.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:49:06.593328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation de62a0ac-10b6-4927-baa4-cfd506ca41fa · outbound

This paper cites an unresolved cited work.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:49:06.584139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ac81c956-41a1-45a2-8d35-5d16be04ea5a · outbound

This paper cites Team, Qwq: Reflect deeply on the boundaries of the unknown, 2024.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Team, Qwq: Reflect deeply on the boundaries of the unknown, 2024

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.574962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 22033834-3263-4e1b-a9a1-2e89373a6fe4 · outbound

This paper cites an unresolved cited work.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:49:06.565458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8e72f584-824f-4846-b0fb-816c9b3397b7 · outbound

This paper cites CuriousLLM: Elevating multi-document question answering with llm-enhanced knowledge graph reasoning,.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation CuriousLLM: Elevating multi-document question answering with llm-enhanced knowledge graph reasoning,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.556560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 034a9a7c-bced-4dfd-bb7a-48cf9ef6e760 · outbound

This paper cites An llm-based multi-stage approach for automated test case generation from user stories,.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation An llm-based multi-stage approach for automated test case generation from user stories,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.547374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 94ca724c-55f5-4fba-a017-0e0cc030f6fd · outbound

This paper cites Improving the domain adaptation of retrieval augmented generation (RAG) models for open domain question an- swering,.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Improving the domain adaptation of retrieval augmented generation (RAG) models for open domain question an- swering,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.537846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 79fdb203-4095-4bd8-a8e2-87f26f1a8e8e · outbound

This paper cites Recent trends in deep learning based open-domain textual question answering systems,.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Recent trends in deep learning based open-domain textual question answering systems,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.528516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 32622231-9c7f-4d8d-81b8-f71a496ade70 · outbound

This paper cites Systematic knowledge injection into large language models via diverse augmentation for domain-specific rag,.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Systematic knowledge injection into large language models via diverse augmentation for domain-specific rag,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.519008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2274332f-cdf8-4a36-ac85-8709aa52a64f · outbound

This paper cites A domain question answering algorithm based on the contrastive language-image pretraining mechanism,.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation A domain question answering algorithm based on the contrastive language-image pretraining mechanism,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.509418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bbc8d433-5ffb-4b4b-84b8-324b4b23c203 · outbound

This paper cites Lightprof: A lightweight reasoning framework for large language model on knowledge graph,.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Lightprof: A lightweight reasoning framework for large language model on knowledge graph,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.499930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d65e2142-fcdb-4bee-8a91-9ddc605518b8 · outbound

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

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Knowledge graph prompting for multi-document question answering,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.490505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6d8fc0fd-0a20-4ac9-aace-e7e4034695f1 · outbound

This paper cites Kimedqa: Towards building knowledge-enhanced medical qa models,.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Kimedqa: Towards building knowledge-enhanced medical qa models,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.480534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8d5b552b-a2e4-485f-87d1-e251ed77f692 · outbound

This paper cites Importance of good data quality in ai business informa- tion systems for iiot enterprises: A data-centric ai approach,.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Importance of good data quality in ai business informa- tion systems for iiot enterprises: A data-centric ai approach,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.470920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eca7a4d3-323d-4a14-a50b-2c8f8f1d7b47 · outbound

This paper cites an unresolved cited work.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:49:06.461318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c4486d0c-71a9-4a44-8a0c-de3153d45489 · outbound

This paper cites Inc., Tidb.ai: An open-source graphrag knowledge base tool , 2024.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Inc., Tidb.ai: An open-source graphrag knowledge base tool , 2024

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.451820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2672932d-775e-4d27-81b8-d5192dbdf6e3 · outbound

This paper cites Contributors, Dify.ai: Open-source llm app development platform , 2023.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Contributors, Dify.ai: Open-source llm app development platform , 2023

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.441890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3e13541b-56a7-4f27-a235-cab0f8cf8bee · outbound

This paper cites Question answering in restricted domains: An overview,.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Question answering in restricted domains: An overview,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.432174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b0cd2c19-31ed-4d48-b49e-a3ad7950874c · outbound

This paper cites A survey on question answering systems over linked data and documents,.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation A survey on question answering systems over linked data and documents,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.421909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d697bfb1-a921-4d9e-ba60-3daaa59bee1d · outbound

This paper cites Large language models encode clinical knowledge,.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Large language models encode clinical knowledge,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.411919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c9b666de-b41f-4284-8c08-381dd45c3e82 · outbound

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

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Retrieval-augmented generation for knowledge- intensive nlp tasks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.402196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 055c9e85-4541-4a87-94ee-8dbdb4265a2a · outbound

This paper cites Knowledge graph-guided retrieval augmented genera- tion,.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Knowledge graph-guided retrieval augmented genera- tion,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.392162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0a77a431-611e-47c5-81cf-935160860d0f · outbound

This paper cites Panda: Performance debugging for databases using LLM agents,.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Panda: Performance debugging for databases using LLM agents,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.382641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3cf80003-b8e9-494f-a68b-8fa601ba9796 · outbound

This paper cites Biomedical knowledge graph-optimized prompt generation for large language models.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Biomedical knowledge graph-optimized prompt generation for large language models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T20:49:06.230912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9827751-5c06-4ae7-b5e4-208dec7a2a12 · outbound

This paper cites Team, Langfuse: Observability for llm applications , Version 3.29.0, 2025.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Team, Langfuse: Observability for llm applications , Version 3.29.0, 2025

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.372503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 71091790-fa88-4c25-9bc8-d21248deabd8 · outbound

This paper cites Ltd., Redis, Version 7.2.5, 2025.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Ltd., Redis, Version 7.2.5, 2025

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.361740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 402e72c5-5d54-4c08-8e07-240b8e9e77a9 · outbound

This paper cites MinIO, Minio: High performance object storage , Version 2025-04- 22T22-12-26Z, 2025.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation MinIO, Minio: High performance object storage , Version 2025-04- 22T22-12-26Z, 2025

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.350558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 32017f40-def5-4cd9-ad93-2345491bb7d6 · outbound

This paper cites ClickHouse, Clickhouse: Open source column-oriented dbms , Ver- sion 25.4.3.22-stable, 2025.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation ClickHouse, Clickhouse: Open source column-oriented dbms , Ver- sion 25.4.3.22-stable, 2025

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.340384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e1978bb1-5d0f-469d-bced-8c1a822b87ce · outbound

This paper cites an unresolved cited work.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:49:06.329525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c7fdd5e2-d725-4f77-8fc1-174be8b1dc60 · outbound

This paper cites Developers, Ragas documentation, 2023.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Developers, Ragas documentation, 2023

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:49:06.319527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d3b29da0-dba1-4962-a340-4531b560b20c · outbound

This paper cites DeepSeek-V3 Technical Report.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation DeepSeek-V3 Technical Report

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T20:49:06.253791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e38a8691-04c5-4f53-b8af-d81683053278 · outbound

This paper cites an unresolved cited work.

DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:49:06.307936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 11c44ac8-0efb-4ea7-b841-d648441a7966 · inbound

DSRAG: A Domain-Specific Retrieval Framework Based on Document-derived Multimodal Knowledge Graph cites this paper.

DSRAG: A Domain-Specific Retrieval Framework Based on Document-derived Multimodal Knowledge Graph DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T17:21:03.136823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a54b8ec-30b7-4c15-b369-2c4bc145682d · inbound

Privacy-Preserving RAG via Multi-Agent Semantic Rewriting: Achieving Confidentiality Without Compromising Contextual Fidelity cites this paper.

Privacy-Preserving RAG via Multi-Agent Semantic Rewriting: Achieving Confidentiality Without Compromising Contextual Fidelity DO-RAG: A Domain-Specific QA Framework Using Knowledge Graph-Enhanced Retrieval-Augmented Generation

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:20:00.994176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.