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Paper Citation Record · LEDGER

Probabilistic Textual Time Series Depression Detection

As of 8 August 2026, this Paper Citation Record lists 5 of 5 outbound references and 1 inbound Pith citation observation for arXiv:2511.04476.

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

pith.paper-citation-record.v1
2511.04476 v2

Coverage vector

measured 5 of 5 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T23:42:40.969267Z

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T00:52:25.185340Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T21:08:58.584720Z

Reference resolution

5 of 5 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved4
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 28a9087b-cf5a-402f-ab36-6f315dbb5b0f · outbound

This paper cites A Topic-Attentive Transformer-based Model For Multimodal Depression Detection.

Probabilistic Textual Time Series Depression Detection A Topic-Attentive Transformer-based Model For Multimodal Depression Detection

Reference 2014

Resolution
unresolved
no resolver link, observed 2026-08-03T23:42:40.581629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T23:42:40.581629Z digest=sha256:f89cebce0f40a822039518140508c863767a2d737fee6659eeb62b9c825d5f1e

Observation 76c7f773-e497-43be-8daf-c01f617dd2ba · outbound

This paper cites Wizard-of- Oz.

Probabilistic Textual Time Series Depression Detection Wizard-of- Oz

Reference 2018

Resolution
malformed identifier
no resolver link, observed 2026-08-03T23:42:40.969267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T23:42:40.969267Z digest=sha256:93f93dfcaed2d48e77b290297e6ddbf5673476833b570e65e5cdb9405f56c809

Observation ecd610f4-8774-4d95-8ba1-8f988f4ab2d4 · outbound

This paper cites InINTERSPEECH 2019, pages 1443– 1447.

Probabilistic Textual Time Series Depression Detection InINTERSPEECH 2019, pages 1443– 1447

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-03T23:42:40.783806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T23:42:40.783806Z digest=sha256:c8dd14db6e48b1b3477ff50455219bd23bddeb97ca3c1016ac95253d3995fe4d

Observation ca0354e9-eb2b-467c-b22f-318fb45b6c16 · outbound

This paper cites The Verbal and Non Verbal Signals of Depression -- Combining Acoustics, Text and Visuals for Estimating Depression Level.

Probabilistic Textual Time Series Depression Detection The Verbal and Non Verbal Signals of Depression -- Combining Acoustics, Text and Visuals for Estimating Depression Level

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-03T23:42:40.670063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T23:42:40.670063Z digest=sha256:cd4da4c358c258a15bf4fb8a85abbfa3a02ca849210b8e1fda06fd36406f3712

Observation dac01a1f-829a-45d0-878e-680f8519c214 · outbound

This paper cites Evgeny A.

Probabilistic Textual Time Series Depression Detection Evgeny A

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-03T23:42:40.902646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T23:42:40.902646Z digest=sha256:73734b6d03403fe7d430f86f67c6a12829497e08e12e6f222045c7fa17896194

Pith citing papers

Observation 97964d83-7b09-448b-974a-54aa711b8b13 · inbound

Fine-tuning LLMs for Passive Depression Severity Estimation from AI Mental Health Dialogue cites this paper.

Fine-tuning LLMs for Passive Depression Severity Estimation from AI Mental Health Dialogue Probabilistic Textual Time Series Depression Detection

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-07-13T02:17:14.207158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T00:52:25.185340Z digest=sha256:a54949dddcb67f813464cf8720ee52be33e278d7fa0c05a4e628423748f40a66