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Paper Citation Record · LEDGER

Evaluating GPT-3.5 and GPT-4 Models on Brazilian University Admission Exams

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2303.17003.

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

pith.paper-citation-record.v1
2303.17003 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-01T07:04:21.555971Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

24
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 24130c4f-afd4-469c-8092-ad287566ac7e · inbound

Prosa: Rubric-Based Evaluation of LLMs on Real User Chats in Brazilian Portuguese cites this paper.

Prosa: Rubric-Based Evaluation of LLMs on Real User Chats in Brazilian Portuguese Evaluating GPT-3.5 and GPT-4 Models on Brazilian University Admission Exams

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:06:04.361499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-09T14:04:21.491683Z digest=sha256:56612befd18f7f010461798702153d6593b59678e604da109f4fb447f318a847

Observation 7888bf43-a33f-42f2-9e93-bcc1fce3cb23 · inbound

Specific Domain Ontology Construction Using Large Language Models cites this paper.

Specific Domain Ontology Construction Using Large Language Models Evaluating GPT-3.5 and GPT-4 Models on Brazilian University Admission Exams

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-06-27T03:30:26.542937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T03:26:15.805999Z digest=sha256:71d49fb15c7a67617704b220babbfe6c32fa93c89ce6e49780e89e116e153930

Observation 39906c6f-46fb-4068-9223-0485559e575e · inbound

BLUEX v2: Benchmarking LLMs on Open-Ended Questions from Brazilian University Entrance Exams cites this paper.

BLUEX v2: Benchmarking LLMs on Open-Ended Questions from Brazilian University Entrance Exams Evaluating GPT-3.5 and GPT-4 Models on Brazilian University Admission Exams

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-04T09:29:43.612702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T09:59:24.703388Z digest=sha256:77d05ad758493cb3f05997637db35ce1b0a32ff577296676d9a5800d856992d1

Observation 8cc3dfe2-3c08-4624-9138-c49696b8fe6d · inbound

BLUEX v2: Benchmarking LLMs on Open-Ended Questions from Brazilian University Entrance Exams cites this paper.

BLUEX v2: Benchmarking LLMs on Open-Ended Questions from Brazilian University Entrance Exams Evaluating GPT-3.5 and GPT-4 Models on Brazilian University Admission Exams

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-07-01T07:05:28.224466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-01T07:04:21.555971Z digest=sha256:85306de956f1bc6a6f610928141e80bd4ca18d11c3e010d586b3661914dbf007