Pith. sign in

Paper Citation Record · LEDGER

Testing the Reliability of ChatGPT for Text Annotation and Classification: A Cautionary Remark

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2304.11085.

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

pith.paper-citation-record.v1
2304.11085 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:19:34.215880Z

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

31
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 7cf48a22-342a-467c-85f3-49af76bb632a · inbound

Reliable Annotations with Less Effort: Evaluating LLM-Human Collaboration in Search Clarifications cites this paper.

Reliable Annotations with Less Effort: Evaluating LLM-Human Collaboration in Search Clarifications Testing the Reliability of ChatGPT for Text Annotation and Classification: A Cautionary Remark

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-06T21:19:34.215880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:19:34.215880Z digest=sha256:ef93abc0c1e664adadd6230f88ae7dd6a750284ffce39e8f1bc1a7fdb1451df2

Observation b0104c6d-5432-4943-8bda-2d5602a919dc · inbound

Guidelines for Empirical Studies in Software Engineering involving Large Language Models cites this paper.

Guidelines for Empirical Studies in Software Engineering involving Large Language Models Testing the Reliability of ChatGPT for Text Annotation and Classification: A Cautionary Remark

Reference 108

Resolution
verified exact
arxiv_id, observed 2026-05-18T22:02:52.236660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T22:02:36.307598Z digest=sha256:7d72c1bac25076c9f9dda6658c849984d83eea713b6798a42f7a338c7ecefff7

Observation aee54fdd-811c-430c-8d40-cbcf204260c6 · inbound

Guidelines for Empirical Studies in Software Engineering involving Large Language Models cites this paper.

Guidelines for Empirical Studies in Software Engineering involving Large Language Models Testing the Reliability of ChatGPT for Text Annotation and Classification: A Cautionary Remark

Reference 108

Resolution
verified exact
arxiv_id, observed 2026-05-25T08:20:31.558775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-25T08:18:18.448122Z digest=sha256:221e4f64eaabe42113a030061dd3305e03c8d986f5d020c0100566b124137cfc

Observation 45d470f2-5af5-4934-89ce-acca95f85e8d · inbound

Noise-Aware Framework for Correcting Corrupted Labels cites this paper.

Noise-Aware Framework for Correcting Corrupted Labels Testing the Reliability of ChatGPT for Text Annotation and Classification: A Cautionary Remark

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-07-03T09:07:47.578105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T10:33:56.216151Z digest=sha256:99b9c01d39beb3e35d5159fc9b56632a78338525de52dcf8fd92db4e020e4800

Observation e2c9264e-c962-4c2f-881f-e285c515485c · inbound

A Data-Centric Framework for Detecting and Correcting Corrupted Labels cites this paper.

A Data-Centric Framework for Detecting and Correcting Corrupted Labels Testing the Reliability of ChatGPT for Text Annotation and Classification: A Cautionary Remark

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-03T09:07:48.095534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T10:31:12.491474Z digest=sha256:c8877b3c387dd5f1ee5ef998485b4a1992f7a7892e52f6d072f7bc53631067e7

Observation 2b785a98-f83d-454b-90c7-6026a02a602c · inbound

A Durability and Cross-Language Transfer Benchmark for a Validated Teaching-Feedback Classification Protocol cites this paper.

A Durability and Cross-Language Transfer Benchmark for a Validated Teaching-Feedback Classification Protocol Testing the Reliability of ChatGPT for Text Annotation and Classification: A Cautionary Remark

Reference 60

Resolution
unresolved
no resolver link, observed 2026-07-14T02:31:04.299071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T02:31:04.299071Z digest=sha256:acae9707eaa46e7f646ed1aa96b91d9f87b48814e33ba6768c907ea80fb9cad6

Observation 1a1a8552-b3d3-4c48-8279-a63ad4e9b875 · inbound

Auditing Differential Visibility of Political Content on TikTok cites this paper.

Auditing Differential Visibility of Political Content on TikTok Testing the Reliability of ChatGPT for Text Annotation and Classification: A Cautionary Remark

Reference 137

Resolution
unresolved
no resolver link, observed 2026-08-01T18:18:13.177995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T18:18:13.177995Z digest=sha256:96e693ffefd181dff0a9229558678cf4848932ab48832609a8bc258b20ee4ab7

Observation 0ddc6f45-88e6-4e93-93bf-b9bac1c69eb6 · inbound

Language Models Agree With Each Other, Not With Readers cites this paper.

Language Models Agree With Each Other, Not With Readers Testing the Reliability of ChatGPT for Text Annotation and Classification: A Cautionary Remark

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-03T10:20:13.152597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:20:13.152597Z digest=sha256:c7ac3e40407b0b327ac3aee4c3adcbfec6350213b379b64595fd558bf7c56338