Pith. sign in

Paper Citation Record · LEDGER

Robust Speech and Natural Language Processing Models for Depression Screening

As of 23 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2412.19072.

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

pith.paper-citation-record.v1
2412.19072 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T01:02:52.641829Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

24 of 24 outbound references displayed

  • verified exact0
  • verified fuzzy17
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7af4f046-3622-408d-a0cc-b9535dd372a4 · outbound

This paper cites Geneva, Switzerland: World Health Organization, 2017, pp.

Robust Speech and Natural Language Processing Models for Depression Screening Geneva, Switzerland: World Health Organization, 2017, pp

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.982319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.547474Z digest=sha256:3d434c0b265f801e518bac247fcfaf3f5d8e81c654eb466c22fcc7be222e5fed

Observation 9d22e836-72dc-4f3f-8cd0-c8433c51092e · outbound

This paper cites Major depressive disorder,.

Robust Speech and Natural Language Processing Models for Depression Screening Major depressive disorder,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.969230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.552245Z digest=sha256:d1ddb734fca28de791bb2925b2abd873be4d1c660c56242333f5ce631a255b85

Observation da17863f-fbc9-4f01-b12b-42516c014dd2 · outbound

This paper cites A Review of Depression and Suicide Risk Assessment Using Speech Analysis,.

Robust Speech and Natural Language Processing Models for Depression Screening A Review of Depression and Suicide Risk Assessment Using Speech Analysis,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.956118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.556531Z digest=sha256:be1353f74a4f34ecc02a408348c65639708184d5e63b5951ec374929e47491d2

Observation c01e3101-9abf-4524-b697-cd3ef9932379 · outbound

This paper cites Hybrid Depression Classification and Estimation from Audio, Video and Text Information,.

Robust Speech and Natural Language Processing Models for Depression Screening Hybrid Depression Classification and Estimation from Audio, Video and Text Information,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.942740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.561083Z digest=sha256:3168f0d15b379c7946ac2abf4b7a490cdd74f72b4af83d20f245fd7a42d33fe1

Observation e1bcdf13-7b9a-411b-822f-b581ecc3d2ad · outbound

This paper cites Detecting Depression using Vocal, Facial and Semantic Communication Cues,.

Robust Speech and Natural Language Processing Models for Depression Screening Detecting Depression using Vocal, Facial and Semantic Communication Cues,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.929251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.565404Z digest=sha256:d74b6ea97fad163517625eddae5c6ce4a469c61e03d8b6c6d1afe4cbd4b9a7dd

Observation 4bcfcb01-83f7-427c-a7d7-6f5e1c244486 · outbound

This paper cites Using Topic Modeling to Improve Prediction of Neuroticism and Depression,.

Robust Speech and Natural Language Processing Models for Depression Screening Using Topic Modeling to Improve Prediction of Neuroticism and Depression,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.914871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.569866Z digest=sha256:4e0e9563ab8296b752027267ff7306e3d51132fba27f25050761209e7f8cf8d0

Observation 55a6c0bf-f7b7-4322-ba24-604d55614a75 · outbound

This paper cites Depression Assessment by Fusing High and Low Level Features from Audio, Video, and Text,.

Robust Speech and Natural Language Processing Models for Depression Screening Depression Assessment by Fusing High and Low Level Features from Audio, Video, and Text,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.902248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.574722Z digest=sha256:22a6d239b8b6bfc06c204bf6c9e65b58101ebfd138aed9bf7b5f197168f8ffbd

Observation 14f9c497-e827-4377-aeea-5c5911248715 · outbound

This paper cites AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition.

Robust Speech and Natural Language Processing Models for Depression Screening AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-11T01:02:52.579063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T01:02:52.579063Z digest=sha256:5dd1abe3b6bde15fd8abfa79ab4a1f25a9857ae475cfa20bbfe7ba3e59bd65c6

Observation 77480ff8-7298-48e1-a527-52e8b2f708cd · outbound

This paper cites CLPsych 2015 Shared Task: Depression and PTSD on Twitter,.

Robust Speech and Natural Language Processing Models for Depression Screening CLPsych 2015 Shared Task: Depression and PTSD on Twitter,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.889700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.583659Z digest=sha256:4f45695cd3d78f7627b4e0ad1f7fef1521830611ba486f272039eb203531141c

Observation f6a7d134-bd50-4cb1-9734-850eff9f3050 · outbound

This paper cites AVEC 2016 - Depression, Mood, and Emotion Recognition Workshop and Challenge.

Robust Speech and Natural Language Processing Models for Depression Screening AVEC 2016 - Depression, Mood, and Emotion Recognition Workshop and Challenge

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-11T01:02:52.587400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T01:02:52.587400Z digest=sha256:432221119c53b627636feece6c464b8c108c92288178eb6b6e95e8f67fd893de

Observation 9f2d1e28-404d-4b20-b70e-e59f54db78c8 · outbound

This paper cites AVEC 2014: 3D Dimensional Affect and Depression Recognition Challenge,.

Robust Speech and Natural Language Processing Models for Depression Screening AVEC 2014: 3D Dimensional Affect and Depression Recognition Challenge,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.876773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.591173Z digest=sha256:74cf8ed547d37477cc65ca9d41c105a74680a479c0c552e51dce64589ca575a6

Observation 76af2ab4-3da7-4773-b66d-d632a80e13a8 · outbound

This paper cites The PHQ-8 as a Measure of Current Depression in the General Population,.

Robust Speech and Natural Language Processing Models for Depression Screening The PHQ-8 as a Measure of Current Depression in the General Population,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.864155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.594892Z digest=sha256:a5ae2a71bc706c5a044f82fdb288f0510dd89283f92fb05dac55488d8aae6f93

Observation 49467bdd-ec3f-488a-b915-b48fd0e82f56 · outbound

This paper cites Gradient-based learning applied to document recognition,.

Robust Speech and Natural Language Processing Models for Depression Screening Gradient-based learning applied to document recognition,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.852323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.598556Z digest=sha256:bbda633974811a6766fc5e29a34575a194d2eea6cf493afc1f6820d11bf257a1

Observation 21d48e14-f884-4be5-9660-8095aea13dee · outbound

This paper cites Long Short-Term Memory,.

Robust Speech and Natural Language Processing Models for Depression Screening Long Short-Term Memory,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.839667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.602289Z digest=sha256:fec33a332636600e3d330dbbca25bccc3d14cbaa6e3d07f5ec1fead24f03898d

Observation 98923424-fc94-434b-8e66-f08ce67ae217 · outbound

This paper cites Regularizing and Optimizing LSTM Language Models.

Robust Speech and Natural Language Processing Models for Depression Screening Regularizing and Optimizing LSTM Language Models

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-11T01:02:52.605946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T01:02:52.605946Z digest=sha256:fac03fc30d45e4d4997b2663486a1ad1950e83089cd1e0a951e8b4c68468a85e

Observation 20e3698d-b26a-4349-b132-ebb913df0802 · outbound

This paper cites Universal Language Model Fine-tuning for Text Classification.

Robust Speech and Natural Language Processing Models for Depression Screening Universal Language Model Fine-tuning for Text Classification

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T01:02:52.609687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T01:02:52.609687Z digest=sha256:dede1a3d22adc460c2e8f5b0fcc83bab919d0e231ac40fea61291a32015cce80

Observation 3d295d01-f913-4494-b9ce-9b9d987daa1f · outbound

This paper cites How Transferable are Neural Networks in NLP Applications?.

Robust Speech and Natural Language Processing Models for Depression Screening How Transferable are Neural Networks in NLP Applications?

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-11T01:02:52.613520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T01:02:52.613520Z digest=sha256:3590a3683b16e6797b053b16c0f8c7f1721be66b4cb98cb9e95405c926a0de26

Observation 17bc1b61-efdf-4410-bb70-072e46b1a327 · outbound

This paper cites Pointer Sentinel Mixture Models.

Robust Speech and Natural Language Processing Models for Depression Screening Pointer Sentinel Mixture Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-11T01:02:52.618456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T01:02:52.618456Z digest=sha256:6059c32c21d29dfbeb96296846801fca6285da912f58d1aac6cde2bf23bd7a78

Observation 61fbda4e-d2e6-42ad-94d6-173bd741dc36 · outbound

This paper cites an unresolved cited work.

Robust Speech and Natural Language Processing Models for Depression Screening Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-08-11T01:02:52.826161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.622444Z digest=sha256:d3dafa46a9c936b1e87fce25e66ed70dec0a1ae7be2bdb2f52fe450ce7bf0b1c

Observation 4bb03209-0bb9-4f91-b433-bb10c9450aeb · outbound

This paper cites Rates of Detection of Mood and Anxiety Disorders in Primary Care: A Descriptive, Cross-Sectional Study,.

Robust Speech and Natural Language Processing Models for Depression Screening Rates of Detection of Mood and Anxiety Disorders in Primary Care: A Descriptive, Cross-Sectional Study,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.811120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.626019Z digest=sha256:71b5c4520265b65f0a85a7cf0d958675810f071af9e29e2c6dd2f8dd4a5c81b3

Observation 3abc8a35-0151-4bfa-9c46-7346ec4a2a05 · outbound

This paper cites Accuracy of general practitioner unassisted detection of depression,.

Robust Speech and Natural Language Processing Models for Depression Screening Accuracy of general practitioner unassisted detection of depression,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.796499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.630387Z digest=sha256:dd43e598c6215b056db944db8653134d2a2b891f9cc68aa4a45a6820f5b68e46

Observation 373e2166-e21d-48cd-86c2-f27098d0bd62 · outbound

This paper cites Clinical diagnosis of depression in primary care: a meta-analysis,.

Robust Speech and Natural Language Processing Models for Depression Screening Clinical diagnosis of depression in primary care: a meta-analysis,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.782499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.633962Z digest=sha256:5e73a67aad3d1322f4b482fd4037e1f93128cacede9cbce818cb5935ea565290

Observation 44d9b739-c535-4eaa-be07-2abbb1f8907e · outbound

This paper cites Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach,.

Robust Speech and Natural Language Processing Models for Depression Screening Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.768645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.638134Z digest=sha256:7a37920948e3b946952cd5c8c7363f0a15ff6109d58dec491068483454fb3213

Observation d5623cd6-504f-44e4-8887-79e675ae5b09 · outbound

This paper cites Fast Implementation of DeLong’s Algorithm for Comparing the Areas Under Correlated Receiver Operating Characteristic Curves,.

Robust Speech and Natural Language Processing Models for Depression Screening Fast Implementation of DeLong’s Algorithm for Comparing the Areas Under Correlated Receiver Operating Characteristic Curves,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T01:02:52.754669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-11T01:02:52.641829Z digest=sha256:831d1491593b128d6afa77def8e4fe28f4191593e2fc15030a52c5c65d873c8c

Pith citing papers

No inbound Pith citation observations are available.