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Paper Citation Record · LEDGER

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language

As of 15 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 1 inbound Pith citation observation for arXiv:2412.10434.

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

pith.paper-citation-record.v1
2412.10434 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:18:35.831633Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-15T00:18:22.361169Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T00:19:35.432035Z

Reference resolution

42 of 42 outbound references displayed

  • verified exact0
  • verified fuzzy16
  • unresolved26
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 39b5970b-9c92-4880-b729-b5f8d1d2e79c · outbound

This paper cites Graph Data Augmentation for Graph Machine Learning: A Survey.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Graph Data Augmentation for Graph Machine Learning: A Survey

Reference 1

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no resolver link, observed 2026-08-11T18:18:34.793340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:18:34.793340Z digest=sha256:b9fab4376f033e3687bd070ad44438591f8208430975f292d9d4457ce12aecdc

Observation 88b69338-22bc-4d38-b505-7a69ead9529b · outbound

This paper cites Unleashing the power of graph data augmentation on covariate dis- tribution shift,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Unleashing the power of graph data augmentation on covariate dis- tribution shift,

Reference 2

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raw_fallback, observed 2026-08-11T18:18:37.667394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T18:18:34.889146Z digest=sha256:9b578bd0fcb97f7c585d2af7c4c30bdc598454979562e4c9ecb6efa155e426d8

Observation 2cd0b2de-9b3e-4a79-985d-e6321f0d398e · outbound

This paper cites Graph databases: An alternative to relational databases in an interconnected big data environment,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Graph databases: An alternative to relational databases in an interconnected big data environment,

Reference 3

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raw_fallback, observed 2026-08-11T18:18:37.649134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T18:18:34.983872Z digest=sha256:4ac7a4b2db0c5f2c8d8f9b155335b58f72a19d587eab44f9c3afa0b30838cd61

Observation defb4f81-5f79-4db5-b9e4-7c013c3e985f · outbound

This paper cites Scalability and performance evaluation of graph database systems: A comparative study of neo4j, janusgraph, memgraph, nebu- lagraph, and tigergraph,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Scalability and performance evaluation of graph database systems: A comparative study of neo4j, janusgraph, memgraph, nebu- lagraph, and tigergraph,

Reference 4

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raw_fallback, observed 2026-08-11T18:18:37.629561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T18:18:34.990014Z digest=sha256:2dbc6b59be68302e55de7a3a733ed7a19e25f8403afb700dcad148c5414482ba

Observation da94dc0f-144f-47a7-a02e-44ff9568a639 · outbound

This paper cites An empirical study on recent graph database systems,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language An empirical study on recent graph database systems,

Reference 5

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raw_fallback, observed 2026-08-11T18:18:37.608803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T18:18:34.995126Z digest=sha256:203b81e6da00e1b9efe387e882c6357ed67b45e4b80a423adf3f565c72166802

Observation e88e3ae6-8bfa-4d9d-a8b9-1407f1e774c5 · outbound

This paper cites Spcql: A semantic parsing dataset for converting natural language into cypher,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Spcql: A semantic parsing dataset for converting natural language into cypher,

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:18:35.001250Z digest=sha256:f10f7b5362be3712c953bb4438ebe1ee9b504f0c16f9a60e4d501b893c8ad2dd

Observation 57d84acb-62da-48d1-a02a-3f0ae5375cc7 · outbound

This paper cites Aligning large language models to a domain-specific graph database for nl2gql,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Aligning large language models to a domain-specific graph database for nl2gql,

Reference 7

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raw_fallback, observed 2026-08-11T18:18:37.549637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T18:18:35.007233Z digest=sha256:b9a5494924e97f1c50db4cf50ada8e96ed82199ed83f2dba603bcef83de055fe

Observation 5ca16612-fb06-4b3d-ae24-9bed540ba27f · outbound

This paper cites r3-NL2GQL: A model coordination and knowledge graph alignment approach for NL2GQL,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language r3-NL2GQL: A model coordination and knowledge graph alignment approach for NL2GQL,

Reference 8

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raw_fallback, observed 2026-08-11T18:18:37.378644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T18:18:35.012986Z digest=sha256:e4867f09dc54e1166319a0faf4ecf1db28e196d121b75865a613301eb448dfab

Observation 698752ba-2d4f-4eb2-8558-7e8f30eda3b4 · outbound

This paper cites Cyspider: A neural semantic parsing corpus with baseline models for property graphs,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Cyspider: A neural semantic parsing corpus with baseline models for property graphs,

Reference 9

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raw_fallback, observed 2026-08-11T18:18:37.251925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T18:18:35.019404Z digest=sha256:f60700cc1acb1134c23ee1267d54300d1b6c6d1d91bdc2f3ef254e5ff950b9b6

Observation ec1b2134-5be2-44fc-a959-0ea83fd9f1cf · outbound

This paper cites Robust text-to-cypher using combination of bert, graphsage, and transformer (cobgt) model,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Robust text-to-cypher using combination of bert, graphsage, and transformer (cobgt) model,

Reference 10

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raw_fallback, observed 2026-08-11T18:18:37.233781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T18:18:35.025141Z digest=sha256:47cc8bdd492c50f14c8ae2e3147fe1500347fa54df420202e2d02a4651bf5858

Observation 4973c14d-83b6-4d7c-bed6-05092c713a07 · outbound

This paper cites Inductive representation learning on large graphs,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Inductive representation learning on large graphs,

Reference 11

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source=pdf_text observed=2026-08-11T18:18:35.029810Z digest=sha256:79890b1a3050db52be145c9be27917d036962dfcf463253867414b469cf9ec4e

Observation a62fe230-26b4-4b98-8325-24728f326bb3 · outbound

This paper cites Kei-cql: A keyword extraction and infilling framework for text to cypher query language translation.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Kei-cql: A keyword extraction and infilling framework for text to cypher query language translation

Reference 12

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raw_fallback, observed 2026-08-11T18:18:37.199084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T18:18:35.034675Z digest=sha256:77db1ce8378aa0eff8f5bd438ae9026d429f99c6bb9879fb47752d7c2e7224b9

Observation e44b8b1b-bc33-4ed1-a653-d26058efae2d · outbound

This paper cites Autotqa: Towards autonomous tabular question answering through multi-agent large language models,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Autotqa: Towards autonomous tabular question answering through multi-agent large language models,

Reference 13

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raw_fallback, observed 2026-08-11T18:18:37.030991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T18:18:35.096073Z digest=sha256:5921f61f67038eab64d4008696b56994cd561dc94777c2ebdad766e61b3ce682

Observation 0084973b-023b-4be7-9b91-5c9020691ae4 · outbound

This paper cites PURPLE: Making a Large Language Model a Better SQL Writer.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language PURPLE: Making a Large Language Model a Better SQL Writer

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:18:35.172641Z digest=sha256:d4c8db6e7de88fc8bf24d6fdf76046ec5d6dbbb9b3f3910cc1cccabbed292660

Observation ca2446bb-cf61-42b2-a67f-885d22046e00 · outbound

This paper cites Online index recommendation for slow queries,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Online index recommendation for slow queries,

Reference 15

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raw_fallback, observed 2026-08-11T18:18:36.891437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T18:18:35.179474Z digest=sha256:76dcf76d8a6a77de14c379fadb27b1d16c59daeef9d4f96b52943a8b7dd73a36

Observation abadbec9-e5cf-45a2-a5d5-98c5f3caac9e · outbound

This paper cites D-Bot: Database Diagnosis System using Large Language Models.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language D-Bot: Database Diagnosis System using Large Language Models

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:18:35.186544Z digest=sha256:32be2ed82d5c8658f181f3ced71e23de9c94ecdfaf74dde116bffe94146cacdd

Observation 36185ef6-0778-49d8-b497-72cfe3e0d94b · outbound

This paper cites GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization

Reference 17

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T18:18:35.192752Z digest=sha256:f0a9a2bd58606a44b66b31e11a2852cca7729be091d3a6b71e5e17b08da63005

Observation 850af4ad-def4-4e3d-8ef9-ac46b9eae680 · outbound

This paper cites Finqa: A training-free dynamic knowledge graph question answering system in finance with llm-based revision,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Finqa: A training-free dynamic knowledge graph question answering system in finance with llm-based revision,

Reference 18

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raw_fallback, observed 2026-08-11T18:18:36.872536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T18:18:35.198903Z digest=sha256:b3c1cd35fce980379427ec29808b00c4d45781604b8523a2bfb0239c64b6afdc

Observation 15513920-055f-4112-9681-b4a9293b9893 · outbound

This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 19

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no resolver link, observed 2026-08-11T18:18:35.204614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:18:35.204614Z digest=sha256:99d2e998a7e1088c9f16e06efd7570daa91d52421623ac2d3d389b0f717a09d2

Observation 53b82de6-6fe6-4d5e-807c-7fdabd828fb3 · outbound

This paper cites Empirical Study of Zero-Shot NER with ChatGPT.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Empirical Study of Zero-Shot NER with ChatGPT

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:18:35.211982Z digest=sha256:ffac9722af0f057cd82bf950d210faa18bdb891a4596e2ee8907e688808d1df8

Observation 6433816b-f98e-45b2-9948-6727aea49204 · outbound

This paper cites Chinese ner using multi-view transformer,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Chinese ner using multi-view transformer,

Reference 21

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raw_fallback, observed 2026-08-11T18:18:36.853314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T18:18:35.218498Z digest=sha256:abed9fb8352737a84de9afef063a742d8d30ab6afd0a6a6798c03e9f3527c9e4

Observation 199d8fd7-17a1-4858-bfe3-bedde2ea0a90 · outbound

This paper cites Large Language Models for Generative Information Extraction: A Survey.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Large Language Models for Generative Information Extraction: A Survey

Reference 22

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no resolver link, observed 2026-08-11T18:18:35.224392Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:18:35.224392Z digest=sha256:d0ed6d777f20282a825868957a020a30da2a15e297c267db3f913526d8c2b880

Observation f67bae77-ba05-430e-a136-40990ef34d71 · outbound

This paper cites Locality-sensitive hashing scheme based on p-stable distributions,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Locality-sensitive hashing scheme based on p-stable distributions,

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-11T18:18:36.783454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T18:18:35.230830Z digest=sha256:06407690b0f85f6563b52b460cbba50ea6a407e6103c046662606a950d70643c

Observation 89c6b0f5-5fe0-4b9c-a9b6-789ceb9fe718 · outbound

This paper cites Parameter-efficient fine-tuning of large- scale pre-trained language models,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Parameter-efficient fine-tuning of large- scale pre-trained language models,

Reference 24

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:18:35.237373Z digest=sha256:cb557a9fcdfb2f289fe2e7f2fe581f334070d9934ce0c34725f50858fac4de73

Observation cb4dbb74-d6f4-41d1-adcb-eef436440e25 · outbound

This paper cites On the effectiveness of parameter-efficient fine-tuning,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language On the effectiveness of parameter-efficient fine-tuning,

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-11T18:18:36.681279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T18:18:35.243519Z digest=sha256:0cfd6733d19d84468a8431f6383a3e3c9632ad31728bd2e644a5ee22a10fbfb3

Observation 73d9f2b1-1150-481d-b22c-069f756c1377 · outbound

This paper cites Qlora: Efficient finetuning of quantized llms,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Qlora: Efficient finetuning of quantized llms,

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:18:35.307607Z digest=sha256:ff8ea2c557ebee185f42d85ce9bf88b7f676959a6e4651aa8fbeb89908a28297

Observation fb982168-a8db-41ad-b826-64c300a1e819 · outbound

This paper cites Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning,

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:18:35.491375Z digest=sha256:9bd23ff7bef83b26b5ec7889c280d437caa6ff90239b45c10a03e34e3449be3c

Observation d85cf07f-25ba-4747-92f8-e397141fc490 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language LoRA: Low-Rank Adaptation of Large Language Models

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:18:35.496476Z digest=sha256:a5d8b75943b27943552769b91045f32bc92c17425e00b09fa8f23d1d25d1eaa8

Observation 9eb562dd-e23e-4e91-a0a0-661afae7b262 · outbound

This paper cites MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:18:35.506927Z digest=sha256:37887914bc803c72a9190a898f854a5a13c7b5f64c61b75b1c7c1d5d35fe037a

Observation ddb585e4-330f-4e00-b217-aa14af94db18 · outbound

This paper cites CHESS: Contextual Harnessing for Efficient SQL Synthesis.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language CHESS: Contextual Harnessing for Efficient SQL Synthesis

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:18:35.512950Z digest=sha256:6f2953f87cc1b7594f3119d128c5bd7b2f4cf6678f3b60d38d1dd17ad4bd7a0f

Observation e4bf2e15-5b1a-44fc-8ee6-a299d36140f4 · outbound

This paper cites Natural language query for technical knowledge graph navigation,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Natural language query for technical knowledge graph navigation,

Reference 32

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raw_fallback, observed 2026-08-11T18:18:36.577856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T18:18:35.518952Z digest=sha256:c4a03919ef27169cb38d2e922fa37647600b507d434b01f11e7915e1a41a3502

Observation 4d6f669c-960e-4f20-aa2f-a05d3873b67b · outbound

This paper cites Language to Logical Form with Neural Attention.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Language to Logical Form with Neural Attention

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:18:35.523992Z digest=sha256:582088a8b9d44d6fd438fb36fd763dd19cf14c46eb3e6180ca9b457179d48ba8

Observation 9c4f8a2e-6c12-41ea-bbf8-5fd1c67c7313 · outbound

This paper cites Incorporating Copying Mechanism in Sequence-to-Sequence Learning.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Incorporating Copying Mechanism in Sequence-to-Sequence Learning

Reference 34

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source=pdf_text observed=2026-08-11T18:18:35.529407Z digest=sha256:ee7ec8fb28c12ce8927fd5caa9750e4b48e2831c037280a2f5e68040b254ec5d

Observation 6d66109e-7220-44d9-ae77-b0eaffa87d4f · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1ccfcbbe-edb3-405c-8a59-66189ea63686 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 36

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Observation 37a0b956-aa57-4339-89a7-c0cb5171a136 · outbound

This paper cites Language models are unsupervised multitask learners,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Language models are unsupervised multitask learners,

Reference 37

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Observation fcffd359-0167-40a2-a902-48d6ce88ecbf · outbound

This paper cites Chase-sql: Multi-path reasoning and preference optimized candidate selection in text-to-sql,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Chase-sql: Multi-path reasoning and preference optimized candidate selection in text-to-sql,

Reference 38

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no resolver link, observed 2026-08-11T18:18:35.551069Z

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Observation 2745635c-fc26-4527-afbc-97d617ec5b3f · outbound

This paper cites The Death of Schema Linking? Text-to-SQL in the Age of Well-Reasoned Language Models.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language The Death of Schema Linking? Text-to-SQL in the Age of Well-Reasoned Language Models

Reference 39

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source=pdf_text observed=2026-08-11T18:18:35.563469Z digest=sha256:7c6518e969866fc7a65bdc2eb99fdf0d268ca8795b740ef18a3df37d3ef1fcb7

Observation 60946983-411d-4493-8fbe-90fa95f39e87 · outbound

This paper cites Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls,.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls,

Reference 40

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no resolver link, observed 2026-08-11T18:18:35.703463Z

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source=pdf_text observed=2026-08-11T18:18:35.703463Z digest=sha256:d4f7f2d03d34a8e809aea6891ed302fdc7d1da9bce1e57f3bf630e020cef2fb5

Observation daa0dc7f-c39f-4168-8642-f29de406eb89 · outbound

This paper cites E-SQL: Direct Schema Linking via Question Enrichment in Text-to-SQL.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language E-SQL: Direct Schema Linking via Question Enrichment in Text-to-SQL

Reference 41

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source=pdf_text observed=2026-08-11T18:18:35.823544Z digest=sha256:b3161eebcd99862ad8b3e74ff83e2506bc35541c2f58a474ab81fb0d65d66427

Observation 44cec781-c011-4754-aad6-0a0d4f32d47f · outbound

This paper cites A Survey on Complex Knowledge Base Question Answering: Methods, Challenges and Solutions.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language A Survey on Complex Knowledge Base Question Answering: Methods, Challenges and Solutions

Reference 42

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no resolver link, observed 2026-08-11T18:18:35.831633Z

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source=pdf_text observed=2026-08-11T18:18:35.831633Z digest=sha256:19b405e11e2bb951f84fc407b0848661e55ae9fcbeeb4db2fb2dc63e043219d5

Observation 2afc5e14-9046-4ceb-9584-bf667afe81aa · outbound

This paper cites CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL.

NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL

Reference 2024

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source=pdf_text observed=2026-08-11T18:18:35.557453Z digest=sha256:9e97e32f22104eeabecf7bab35d87a1bff47bd1bba0850044abfbb9e0bef858e

Pith citing papers

Observation 577659fd-a796-4097-b822-644df586125a · inbound

Natural Language Interfaces for Spatial and Temporal Databases: A Comprehensive Overview of Methods, Taxonomy, and Future Directions cites this paper.

Natural Language Interfaces for Spatial and Temporal Databases: A Comprehensive Overview of Methods, Taxonomy, and Future Directions NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language

Reference 24

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verified exact
arxiv_id, observed 2026-05-15T00:19:35.433560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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