Paper Citation Record · LEDGER

Explainable Depression Detection using Masked Hard Instance Mining

As of 7 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 1 inbound Pith citation observation for arXiv:2505.24609.

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

pith.paper-citation-record.v1
2505.24609 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:23:24.033306Z

measured 40 of 40 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 2026-08-07T12:23:21.293556Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T12:23:24.188514Z

Reference resolution

39 of 39 outbound references displayed

verified exact2
verified fuzzy33
unresolved4
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 91722d6a-d8ca-4ac5-98c9-e378041eb375 · outbound

This paper cites Despite its widespread impact, many individuals re- main unaware of their susceptibility to depression, which of- ten leads to delayed diagnosis and treatment [2].

Explainable Depression Detection using Masked Hard Instance Mining Despite its widespread impact, many individuals re- main unaware of their susceptibility to depression, which of- ten leads to delayed diagnosis and treatment [2]

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:27.723911Z

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Observation e63051aa-b397-48b7-af82-20fa4e2e6503 · outbound

This paper cites Explainable Depression Detection using Masked Hard Instance Mining.

Explainable Depression Detection using Masked Hard Instance Mining Explainable Depression Detection using Masked Hard Instance Mining

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:23:24.234682Z

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Observation 630dc905-ccc9-4f3d-a11d-51e070a0dbfb · outbound

This paper cites We find that this procedure often suffer from overfitting, especially on low-data regime.

Explainable Depression Detection using Masked Hard Instance Mining We find that this procedure often suffer from overfitting, especially on low-data regime

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:27.624007Z

Source-reported events for the cited work

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Observation 976c9a94-53f3-40a9-916a-81d5f5495c95 · outbound

This paper cites Datasets To benchmark the performance of our method, we have cho- sen two datasets for benchmarking: the DAIC-WOZ [11] and the Thai-Maywe dataset [10].

Explainable Depression Detection using Masked Hard Instance Mining Datasets To benchmark the performance of our method, we have cho- sen two datasets for benchmarking: the DAIC-WOZ [11] and the Thai-Maywe dataset [10]

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:27.507480Z

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Observation f7a53c7e-de39-4d09-b1ac-c1aa265609c9 · outbound

This paper cites Model Performance on the Thai-Maywe dataset Table 1 shows the prediction performance on the Thai-Maywe dataset of our method compared to other baselines.

Explainable Depression Detection using Masked Hard Instance Mining Model Performance on the Thai-Maywe dataset Table 1 shows the prediction performance on the Thai-Maywe dataset of our method compared to other baselines

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:27.379692Z

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Observation 742308b1-bf6f-4116-9f56-a74c1bd99655 · outbound

This paper cites The pipeline was specifically de- signed to promote diversified attending pattern, thereby less prone to overfitting in low-data settings.

Explainable Depression Detection using Masked Hard Instance Mining The pipeline was specifically de- signed to promote diversified attending pattern, thereby less prone to overfitting in low-data settings

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:27.308951Z

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Observation f0ba8cb0-f6f4-46aa-bf4d-47dc80a8a26b · outbound

This paper cites an unresolved cited work.

Explainable Depression Detection using Masked Hard Instance Mining Unresolved cited work

Reference 7

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Observation eba284c0-73e8-4757-963a-488c5afc6b52 · outbound

This paper cites Depression and other common mental disorders: global health estimates,.

Explainable Depression Detection using Masked Hard Instance Mining Depression and other common mental disorders: global health estimates,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:27.031082Z

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Observation c480fe93-e647-4142-ad85-beb6c4391c97 · outbound

This paper cites Projections of global mortality and burden of disease from 2002 to 2030,.

Explainable Depression Detection using Masked Hard Instance Mining Projections of global mortality and burden of disease from 2002 to 2030,

Reference 9

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Observation 60a42900-bdc7-4e0c-8b2d-cb5e51b7ac25 · outbound

This paper cites A text classification framework for simple and effective early depression detection over social media streams,.

Explainable Depression Detection using Masked Hard Instance Mining A text classification framework for simple and effective early depression detection over social media streams,

Reference 10

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Source-reported events for the cited work

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Observation 1647a772-0e96-4662-a971-1b567d268cd4 · outbound

This paper cites Real-time acoustic based depression detection using machine learning techniques,.

Explainable Depression Detection using Masked Hard Instance Mining Real-time acoustic based depression detection using machine learning techniques,

Reference 11

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Observation b9d162b9-df6a-45dc-938b-91ed0b7a44bf · outbound

This paper cites Deep learning for depression detection of twitter users,.

Explainable Depression Detection using Masked Hard Instance Mining Deep learning for depression detection of twitter users,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:26.629026Z

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Observation 0e941485-e572-487a-b885-adb654410fa3 · outbound

This paper cites Detecting linguistic traces of depression in topic-restricted text: Attending to self-stigmatized depression with nlp,.

Explainable Depression Detection using Masked Hard Instance Mining Detecting linguistic traces of depression in topic-restricted text: Attending to self-stigmatized depression with nlp,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:26.498249Z

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Observation e21bafa1-933e-4214-9391-f5bb3bc024a2 · outbound

This paper cites Xa-bilstm: a deep learning approach for depression detection in imbalanced data,.

Explainable Depression Detection using Masked Hard Instance Mining Xa-bilstm: a deep learning approach for depression detection in imbalanced data,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:26.412814Z

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Observation a8c5a873-1ae3-451e-ae38-d28f49bbbc8f · outbound

This paper cites Automatic depression severity assessment with deep learning using parameter-efficient tuning,.

Explainable Depression Detection using Masked Hard Instance Mining Automatic depression severity assessment with deep learning using parameter-efficient tuning,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:26.339711Z

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Observation 31178653-1b58-47ea-8c25-290bbea85c45 · outbound

This paper cites Explainable depression symp- tom detection in social media,.

Explainable Depression Detection using Masked Hard Instance Mining Explainable depression symp- tom detection in social media,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:26.259022Z

Source-reported events for the cited work

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Observation 4b681f37-78e1-4d5c-a703-bcafde8e6b39 · outbound

This paper cites An application for mental health monitoring using facial, voice, and questionnaire information,.

Explainable Depression Detection using Masked Hard Instance Mining An application for mental health monitoring using facial, voice, and questionnaire information,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:26.162961Z

Source-reported events for the cited work

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Observation 0b36086a-4822-4d8c-b4e3-bc26ae6aff4a · outbound

This paper cites The Distress Analysis Interview Corpus of human and computer interviews.

Explainable Depression Detection using Masked Hard Instance Mining The Distress Analysis Interview Corpus of human and computer interviews

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:26.055501Z

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Observation d2c49528-dae1-4fe8-9434-0076ce512a62 · outbound

This paper cites Multiple instance learning: algorithms and applica- tions,.

Explainable Depression Detection using Masked Hard Instance Mining Multiple instance learning: algorithms and applica- tions,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:25.943627Z

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Observation 48d7ace7-5ea6-40af-9e39-17bbf792c690 · outbound

This paper cites Attention-based deep mul- tiple instance learning,.

Explainable Depression Detection using Masked Hard Instance Mining Attention-based deep mul- tiple instance learning,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:25.876164Z

Source-reported events for the cited work

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Observation bb5a5b3d-05f3-4f9e-90b6-36194e30605f · outbound

This paper cites Multiple instance learning framework with masked hard instance mining for whole slide image classification,.

Explainable Depression Detection using Masked Hard Instance Mining Multiple instance learning framework with masked hard instance mining for whole slide image classification,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:25.752192Z

Source-reported events for the cited work

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Observation 1b944895-0d5c-4fbe-a2c6-7de67c24dfca · outbound

This paper cites P-tuning: Prompt tuning can be comparable to fine-tuning across scales and tasks,.

Explainable Depression Detection using Masked Hard Instance Mining P-tuning: Prompt tuning can be comparable to fine-tuning across scales and tasks,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:25.668237Z

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Observation 726ead49-61b8-4c0f-8300-89b6eddc3192 · outbound

This paper cites Universal sentence encoder for English,.

Explainable Depression Detection using Masked Hard Instance Mining Universal sentence encoder for English,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:25.562215Z

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Observation 7aa96803-507e-464a-a171-eee31f969120 · outbound

This paper cites Multi instance neural networks,.

Explainable Depression Detection using Masked Hard Instance Mining Multi instance neural networks,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:25.432556Z

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Observation 46d50f0a-b470-4ca3-8d15-b18242c428c9 · outbound

This paper cites A brief introduction to weakly supervised learning,.

Explainable Depression Detection using Masked Hard Instance Mining A brief introduction to weakly supervised learning,

Reference 25

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Observation d78e4f9b-134b-484e-8bdf-854841de86fa · outbound

This paper cites Trans- mil: Transformer based correlated multiple instance learning for whole slide image classification,.

Explainable Depression Detection using Masked Hard Instance Mining Trans- mil: Transformer based correlated multiple instance learning for whole slide image classification,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:25.342018Z

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Observation 76cebad0-14fd-41c4-90d3-4f761181efa2 · outbound

This paper cites Neural machine transla- tion by jointly learning to align and translate,.

Explainable Depression Detection using Masked Hard Instance Mining Neural machine transla- tion by jointly learning to align and translate,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:25.243009Z

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Observation 7df47382-a223-4bef-92fd-10c1f47223f1 · outbound

This paper cites What does BERT look at? an analysis of BERT‘s attention,.

Explainable Depression Detection using Masked Hard Instance Mining What does BERT look at? an analysis of BERT‘s attention,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:25.157073Z

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Observation 36dea466-9500-4f1b-be68-1aa4d114f1da · outbound

This paper cites Mpnet: Masked and permuted pre-training for language understanding,.

Explainable Depression Detection using Masked Hard Instance Mining Mpnet: Masked and permuted pre-training for language understanding,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:24.386711Z

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Observation e39c83bf-511e-4024-a359-34509155edac · outbound

This paper cites Human attention maps for text classification: Do humans and neural networks focus on the same words?.

Explainable Depression Detection using Masked Hard Instance Mining Human attention maps for text classification: Do humans and neural networks focus on the same words?

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:24.932300Z

Source-reported events for the cited work

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Observation f4a684b7-6d65-467b-8cbe-03fe76c3e51d · outbound

This paper cites On exploring attention-based explanation for transformer models in text clas- sification,.

Explainable Depression Detection using Masked Hard Instance Mining On exploring attention-based explanation for transformer models in text clas- sification,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:24.842103Z

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.

Observation 2dc265cd-c6ad-4e1c-9858-e5af1573eec8 · outbound

This paper cites Towards automatic text- based estimation of depression through symptom prediction,.

Explainable Depression Detection using Masked Hard Instance Mining Towards automatic text- based estimation of depression through symptom prediction,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:24.745345Z

Source-reported events for the cited work

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Observation f01d5d85-80f4-4a3b-8007-9428e7cd0224 · outbound

This paper cites The phq-8 as a measure of current depression in the general population,.

Explainable Depression Detection using Masked Hard Instance Mining The phq-8 as a measure of current depression in the general population,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:24.662217Z

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Observation 47c79ecc-8bd4-4ca9-b651-675953b3b9e0 · outbound

This paper cites The hamilton rating scale for depression,.

Explainable Depression Detection using Masked Hard Instance Mining The hamilton rating scale for depression,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:24.591860Z

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Observation 6ef006b3-6f7c-43d4-b242-aef17557d3b1 · outbound

This paper cites The dsm-5: Classifi- cation and criteria changes,.

Explainable Depression Detection using Masked Hard Instance Mining The dsm-5: Classifi- cation and criteria changes,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:24.483233Z

Source-reported events for the cited work

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Observation 214ab9db-d9c0-4bd5-bd4e-83bdf9e5b8ed · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Explainable Depression Detection using Masked Hard Instance Mining RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 36

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This paper cites WangchanBERTa: Pretraining transformer-based Thai Language Models.

Explainable Depression Detection using Masked Hard Instance Mining WangchanBERTa: Pretraining transformer-based Thai Language Models

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:23:24.128350Z

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Observation a610d8c1-5fff-4dd2-bb81-8fb8a16ba711 · outbound

This paper cites ConGen: Unsupervised control and generalization distillation for sentence representation,.

Explainable Depression Detection using Masked Hard Instance Mining ConGen: Unsupervised control and generalization distillation for sentence representation,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:24.308078Z

Source-reported events for the cited work

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Observation e1db9a41-638d-4d0d-ab8b-7de0abdbec29 · outbound

This paper cites Available: https://aclanthology.org/W19-4828/.

Explainable Depression Detection using Masked Hard Instance Mining Available: https://aclanthology.org/W19-4828/

Reference 286

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:23:25.005458Z

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.

Pith citing papers

Observation e63051aa-b397-48b7-af82-20fa4e2e6503 · inbound