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Paper Citation Record · LEDGER

Fact-Consistency Evaluation of Text-to-SQL Generation for Business Intelligence Using Exaone 3.5

As of 21 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 0 inbound Pith citation observations for arXiv:2505.00060.

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

pith.paper-citation-record.v1
2505.00060 v1

Coverage vector

measured 7 of 7 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:03:02.941435Z

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

7 of 7 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 83cfd022-246e-4869-a456-bf113eecc912 · outbound

This paper cites Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning.

Fact-Consistency Evaluation of Text-to-SQL Generation for Business Intelligence Using Exaone 3.5 Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-16T05:03:02.910694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:03:02.910694Z digest=sha256:8718a1081e1085608946dda9f3b31bc26b9a73052796a14fd4f2ead5db4fb9c3

Observation 950fa921-4768-4387-907b-3611c268f8fc · outbound

This paper cites Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task.

Fact-Consistency Evaluation of Text-to-SQL Generation for Business Intelligence Using Exaone 3.5 Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-16T05:03:02.916444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:03:02.916444Z digest=sha256:89d652f0e8c34db128e3ce02537ae4d85b8810410d7eb5863b6a4463b3e629f2

Observation 5c1a75eb-f96e-473b-908f-6420ddc6867d · outbound

This paper cites SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-DomainText-to-SQL Task.

Fact-Consistency Evaluation of Text-to-SQL Generation for Business Intelligence Using Exaone 3.5 SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-DomainText-to-SQL Task

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-16T05:03:02.921287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:03:02.921287Z digest=sha256:c4fd01aee923dd95eee0be002458dd0b60f76897c2b9cec1992d36d5ce09586e

Observation 9354b100-0240-4302-8510-97fb3eaeb9bc · outbound

This paper cites Bi-fidelity Variational Auto-encoder for Uncertainty Quantification.

Fact-Consistency Evaluation of Text-to-SQL Generation for Business Intelligence Using Exaone 3.5 Bi-fidelity Variational Auto-encoder for Uncertainty Quantification

Reference 4

Resolution
metadata mismatch
local_arxiv, observed 2026-08-16T05:03:03.073556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-16T05:03:02.926070Z digest=sha256:0029b0afe96e7e951471142ceb87575a28d4d1d1b90befa77190560f89a7d223

Observation d60a8a2d-4832-43f8-bb95-f27b5f9f71c6 · outbound

This paper cites Unraveling the nature of the novel $\mathbf{T_{cs}}$ and $\mathbf{T_{c\bar s}}$ tetraquark candidates.

Fact-Consistency Evaluation of Text-to-SQL Generation for Business Intelligence Using Exaone 3.5 Unraveling the nature of the novel $\mathbf{T_{cs}}$ and $\mathbf{T_{c\bar s}}$ tetraquark candidates

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-16T05:03:02.930726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:03:02.930726Z digest=sha256:539a8facaca899baaffee4228a85ca9652af9af0dabf9f51462e315ab45c1c82

Observation d9e6e0e3-4b6a-45b5-9ef4-3018e746ab1c · outbound

This paper cites Scaling Instruction-Finetuned Language Models.

Fact-Consistency Evaluation of Text-to-SQL Generation for Business Intelligence Using Exaone 3.5 Scaling Instruction-Finetuned Language Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-16T05:03:02.935903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:03:02.935903Z digest=sha256:ea23aa579a445db22b0fda761b3df21ef759abf12d1ba212cbfb2a0994209717

Observation 03eea818-362c-4076-abc4-8e15bb4a5c58 · outbound

This paper cites Exaone 3.5: Series of large language models for r eal-world use cases.

Fact-Consistency Evaluation of Text-to-SQL Generation for Business Intelligence Using Exaone 3.5 Exaone 3.5: Series of large language models for r eal-world use cases

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-16T05:03:02.941435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:03:02.941435Z digest=sha256:38a5acdef103208a514e5727b9b8228bb7d34ff2fb7c511957cea503293ff523

Pith citing papers

No inbound Pith citation observations are available.