Pith. sign in

Paper Citation Record · LEDGER

Automated Annotation with Generative AI Requires Validation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2306.00176.

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

pith.paper-citation-record.v1
2306.00176 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 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 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:16:55.941717Z

measured 1 of 1 external citation measurements

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

Source: pith, 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

35
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c11851c0-648c-4050-96c7-615eaf7e6704 · inbound

Structuring Radiology Reports: Challenging LLMs with Lightweight Models cites this paper.

Structuring Radiology Reports: Challenging LLMs with Lightweight Models Automated Annotation with Generative AI Requires Validation

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T12:16:55.941717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:16:55.941717Z digest=sha256:8212621d29c86c7d3478a5a426e5beade5a013c766c05bc558f96ea055e4e398

Observation dbac3210-2636-4df4-aac0-fe356c764e7f · 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 Automated Annotation with Generative AI Requires Validation

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-06T21:19:33.977301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:19:33.977301Z digest=sha256:9df7743390c7bdcc1aabbd782c3b5003589161011966d8402157a526bee8a8e2

Observation 4eb555af-5dae-4ced-a911-d577104fadff · inbound

Co-DETECT: Collaborative Discovery of Edge Cases in Text Classification cites this paper.

Co-DETECT: Collaborative Discovery of Edge Cases in Text Classification Automated Annotation with Generative AI Requires Validation

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T19:38:03.033719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:38:03.033719Z digest=sha256:7107168890981f4f5c5f4c9ce24e49c4c0a722447a7aa0360dfa420427f77031

Observation 222f21f9-e942-4796-81f8-6699b50b9caa · 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 Automated Annotation with Generative AI Requires Validation

Reference 100

Resolution
verified exact
arxiv_id, observed 2026-05-18T22:02:52.269813Z

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=2026-05-18T22:02:36.307598Z digest=sha256:571ca9026025b53ce7da4b535bf8d5a5a17988065665048fc340debb385f622a

Observation c1834796-0370-46c4-ac36-3cbe7a26b434 · 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 Automated Annotation with Generative AI Requires Validation

Reference 100

Resolution
verified exact
arxiv_id, observed 2026-05-25T08:20:31.730528Z

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=2026-05-25T08:18:18.448122Z digest=sha256:ceb549806e315819a6711716f88adf7a0ee79b2862ea9e297cc26748629a97bf

Observation dcf7303c-583f-4dc1-884e-a31c34fd64c2 · inbound

Do We Still Need Humans in the Loop? Comparing Human and LLM Annotation in Active Learning for Hostility Detection cites this paper.

Do We Still Need Humans in the Loop? Comparing Human and LLM Annotation in Active Learning for Hostility Detection Automated Annotation with Generative AI Requires Validation

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-10T13:40:27.011321Z

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=2026-05-10T13:38:02.450128Z digest=sha256:84cfc1489dec06071e7f4b8b44c5df6190e8304cf96294ba3c664315adaafe47

Observation 6cd86732-cf4b-4ac6-872b-c79084c57c03 · inbound

Do We Still Need Humans in the Loop? Comparing Human and LLM Annotation in Active Learning for Hostility Detection cites this paper.

Do We Still Need Humans in the Loop? Comparing Human and LLM Annotation in Active Learning for Hostility Detection Automated Annotation with Generative AI Requires Validation

Reference 9

Resolution
unresolved
no resolver link, observed 2026-07-12T20:35:52.598345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T20:35:52.598345Z digest=sha256:00c39b76a27e7203d98609261edf68834a540e66b1753c85315334c2ff4ac10e

Observation 919b8be2-0722-4637-b572-983813e721b2 · inbound

LLM Predictive Scoring and Validation: Inferring Experience Ratings from Unstructured Text cites this paper.

LLM Predictive Scoring and Validation: Inferring Experience Ratings from Unstructured Text Automated Annotation with Generative AI Requires Validation

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-10T13:55:28.694422Z

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=2026-05-10T13:54:24.082141Z digest=sha256:41015c9526620780ac9c7e35b9bbc5dfdf50e8f48ab2dd8aab3c3c3894706941

Observation 548b3691-7f42-4fc3-903d-e6425ccb8a9b · inbound

LegalBench-BR: A Benchmark for Evaluating Large Language Models on Brazilian Legal Decision Classification cites this paper.

LegalBench-BR: A Benchmark for Evaluating Large Language Models on Brazilian Legal Decision Classification Automated Annotation with Generative AI Requires Validation

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T11:56:27.318769Z

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=2026-05-10T04:27:23.053818Z digest=sha256:8835394a1c56747d1340d4eada02e312f56dcd32e69dca466c2d6fd2e7292de9

Observation b0d4beca-0fc7-4b20-bce0-2db67f221357 · inbound

How Much Does Persuasion Strategy Matter? LLM-Annotated Evidence from Charitable Donation Dialogues cites this paper.

How Much Does Persuasion Strategy Matter? LLM-Annotated Evidence from Charitable Donation Dialogues Automated Annotation with Generative AI Requires Validation

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-14T22:28:04.054794Z

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=2026-05-14T22:26:49.010635Z digest=sha256:399b12af50095e97db4478e5d7647e886ba86b365f54a1bfa05f45b160be0d25

Observation 6e18edc4-5502-4f03-98b4-8278c1ad5771 · inbound

What Your Posts Reveal: A Benchmark and Agentic Framework for User-Level Privacy Leakage on Social Media cites this paper.

What Your Posts Reveal: A Benchmark and Agentic Framework for User-Level Privacy Leakage on Social Media Automated Annotation with Generative AI Requires Validation

Reference 38

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T17:17:14.873273Z

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=2026-06-27T22:08:24.018844Z digest=sha256:1eeec2edeeee8f78eff9656861875ae33887d66497038c34d275eb96a0f51b63

Observation de043efc-4110-4a25-aaff-0f1d876ab016 · inbound

The Model as One Rater Among Several: Measuring Political Positions in Data-Sparse Regions with a Language-Model Panel cites this paper.

The Model as One Rater Among Several: Measuring Political Positions in Data-Sparse Regions with a Language-Model Panel Automated Annotation with Generative AI Requires Validation

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-07-04T12:39:49.405965Z

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=2026-06-26T06:23:58.873694Z digest=sha256:a10bb999ec1522bf553d0f50cf89dd61d54961f5af752efb36f1f00cbf8af0ba

Observation 95bd24b1-d14b-4697-a501-2da8904b2673 · inbound

Correct codes for the wrong reasons? validating LLMs as measurement instruments for theoretical constructs cites this paper.

Correct codes for the wrong reasons? validating LLMs as measurement instruments for theoretical constructs Automated Annotation with Generative AI Requires Validation

Reference 49

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T16:25:50.001677Z

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=2026-06-30T00:40:09.452943Z digest=sha256:d1acfb7bf553fa22529e72461fc6913ec5c0e7b0ccb48571d500cf0a17ad1aef

Observation c3ce0b92-1081-4b08-b117-5d09ef323d36 · inbound

Talking Politics with Artificial Intelligence cites this paper.

Talking Politics with Artificial Intelligence Automated Annotation with Generative AI Requires Validation

Reference 17

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T03:26:28.410008Z

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=2026-07-02T03:24:16.158417Z digest=sha256:5f4a106e7ee56a7456c52e7a5ce873e9842cd32d01f23283f54a88992cf79b78

Observation 64df4f0b-1e9f-4b55-9e2d-b3b396816c3d · inbound

Grounded Event Extraction from SEC 8-K Filings with a Fine-Grained Taxonomy cites this paper.

Grounded Event Extraction from SEC 8-K Filings with a Fine-Grained Taxonomy Automated Annotation with Generative AI Requires Validation

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-07-10T09:06:59.077046Z

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=2026-07-10T08:59:30.965660Z digest=sha256:800b14a2f81fa64895dee8dd3060c45f1b56fbc26ddc73bad36f52c2d3b310bb

Observation 45012712-32f7-4e7b-8ced-0951a8a400c8 · 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 Automated Annotation with Generative AI Requires Validation

Reference 56

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:db972f1f7de8eeb172c7e2d712d8d2ce17e4168b143c9ce28d86aea6df712c79

Observation 5ced4911-8529-4d80-a3a4-0cf03fe00d9a · inbound

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

Auditing Differential Visibility of Political Content on TikTok Automated Annotation with Generative AI Requires Validation

Reference 138

Resolution
unresolved
no resolver link, observed 2026-08-01T18:18:13.296342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T18:18:13.296342Z digest=sha256:8449161eab70c460d3ea1e04fe0e2a696200146cb13e505f7da98b973bdd10ed