Paper Citation Record · LEDGER

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection

As of 17 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2604.10181.

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

pith.paper-citation-record.v1
2604.10181 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-10T15:46:58.566821Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T15:46:58.566821Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-11T09:51:00.712579Z

Reference resolution

34 of 34 outbound references displayed

verified exact3
verified fuzzy30
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b537bfb3-a2d6-4cde-a294-3a903e966b27 · outbound

This paper cites Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-05-11T09:51:00.715166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bad4ceb3-2477-458f-a1c0-4f04e482125c · outbound

This paper cites This mecha- nism selectively enhances clinically significant segments while suppressing neutral or irrelevant content.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection This mecha- nism selectively enhances clinically significant segments while suppressing neutral or irrelevant content

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.915100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9095db27-430f-44bd-8480-cd5177ceb906 · outbound

This paper cites Transformer(Qwen).

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Transformer(Qwen)

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.917803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fc322aed-e126-40da-bb97-e3058f3f8cb6 · outbound

This paper cites Experiments on PDCD2025 and DAIC- WOZ show that ACMG outperforms baseline models in both accuracy and F1.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Experiments on PDCD2025 and DAIC- WOZ show that ACMG outperforms baseline models in both accuracy and F1

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.923765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a5626741-32d6-4d2f-895b-267be4a91e5d · outbound

This paper cites They were not used to create any core research con- tent, results, or arguments.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection They were not used to create any core research con- tent, results, or arguments

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.920693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ec6c98a1-5129-4799-bbb1-48e8022a98e3 · outbound

This paper cites Burden of de- pressive disorders by country, sex, age, and year: findings from the global burden of disease study 2010.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Burden of de- pressive disorders by country, sex, age, and year: findings from the global burden of disease study 2010

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.970510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fe6ece28-08e9-419c-8c1e-87361661d637 · outbound

This paper cites Research domain crite- ria (rdoc): toward a new classification framework for research on mental disorders.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Research domain crite- ria (rdoc): toward a new classification framework for research on mental disorders

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:50:05.759143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3e3707b7-4768-4744-8004-3ba5a34ca184 · outbound

This paper cites Detecting depres- sion with audio/text sequence modeling of interviews.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Detecting depres- sion with audio/text sequence modeling of interviews

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:50:05.743466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2394ec0f-a734-42c4-af63-380f21a0e6c1 · outbound

This paper cites Ecapa- tdnn based depression detection from clinical speech.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Ecapa- tdnn based depression detection from clinical speech

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.983521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3ed62231-ef32-4cc1-bfe4-cc8110880d0a · outbound

This paper cites Depression detection in speech using transformer and parallel convolutional neural networks.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Depression detection in speech using transformer and parallel convolutional neural networks

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.941251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 18b9ddbf-53e3-40a4-a0e4-73e6be08b227 · outbound

This paper cites Speechformer-ctc: Se- quential modeling of depression detection with speech temporal classification.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Speechformer-ctc: Se- quential modeling of depression detection with speech temporal classification

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.986443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 130decd9-62cf-4431-958e-298031d78e5f · outbound

This paper cites wav2vec: Unsupervised Pre-training for Speech Recognition.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection wav2vec: Unsupervised Pre-training for Speech Recognition

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:51:00.710066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a9af8736-5aab-4853-9710-20fb94bbdea6 · outbound

This paper cites Hubert: Self-supervised speech represen- tation learning by masked prediction of hidden units.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Hubert: Self-supervised speech represen- tation learning by masked prediction of hidden units

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.973401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 941fe629-fcb2-4703-82f9-b2e9c1975ea2 · outbound

This paper cites Wavlm: Large-scale self- supervised pre-training for full stack speech processing.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Wavlm: Large-scale self- supervised pre-training for full stack speech processing

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.976698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 72b898e4-98ff-496c-93ed-2e6746167797 · outbound

This paper cites Self-supervised represen- tations in speech-based depression detection.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Self-supervised represen- tations in speech-based depression detection

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.979768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8c2dd05d-5bf4-41ea-8de3-618f8accd03d · outbound

This paper cites Self-Supervised Embeddings for Detecting Individual Symptoms of Depression.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Self-Supervised Embeddings for Detecting Individual Symptoms of Depression

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:50:05.773142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4fb439be-31ac-486a-a8b8-6e1396658909 · outbound

This paper cites Bert: Pre- training of deep bidirectional transformers for language under- standing.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Bert: Pre- training of deep bidirectional transformers for language under- standing

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.967424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d13bcc55-0973-4e21-a75a-21240c37d271 · outbound

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

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-05-11T09:51:00.695770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 942434f5-9564-43bf-adf6-a44c10d32011 · outbound

This paper cites Zero-Shot Speech-Based Depression and Anxiety Assessment with LLMs.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Zero-Shot Speech-Based Depression and Anxiety Assessment with LLMs

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.952545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 44ed62b3-5a46-49f1-86e6-e9fc9e5d499c · outbound

This paper cites Glottal source features for auto- matic speech-based depression assessment.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Glottal source features for auto- matic speech-based depression assessment

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.955486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b327b8bd-e025-4d31-828d-5d6df8bf6e87 · outbound

This paper cites A time-frequency channel attention and vectorization network for automatic depression level prediction.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection A time-frequency channel attention and vectorization network for automatic depression level prediction

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.929695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d4468d45-b805-4586-8cd2-43b83f3793c7 · outbound

This paper cites V ocal acoustic biomarkers of depression severity and treatment response.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection V ocal acoustic biomarkers of depression severity and treatment response

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.960960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ba2fbb57-5a66-4396-9896-a3599814fce0 · outbound

This paper cites A meta-analysis of correlations between depression and first person singular pronoun use.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection A meta-analysis of correlations between depression and first person singular pronoun use

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.964139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 38f1ffff-6c0a-42ff-8dae-c914eba532cd · outbound

This paper cites Depression, negative emotionality, and self-referential language: A multi-lab, multi-measure, and multi-language-task research synthesis.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Depression, negative emotionality, and self-referential language: A multi-lab, multi-measure, and multi-language-task research synthesis

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:50:05.768363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 93f4b39d-8586-42a8-a6a3-59159f587df6 · outbound

This paper cites Investigating acoustic-textual emo- tional inconsistency information for automatic depression detec- tion.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Investigating acoustic-textual emo- tional inconsistency information for automatic depression detec- tion

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.926545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 22f3b60e-807e-49cb-9cc2-036c771d47c4 · outbound

This paper cites Speaker normalization for self-supervised speech emotion recognition.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Speaker normalization for self-supervised speech emotion recognition

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.949661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3d618064-18f9-4a19-b41e-3df928261dfb · outbound

This paper cites Speech emotion recognition using self-supervised features.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Speech emotion recognition using self-supervised features

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.943881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 03bc86c7-7e92-42d6-92df-06ddb87bf798 · outbound

This paper cites Comparative analy- ses of bert, roberta, distilbert, and xlnet for text-based emotion recognition.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Comparative analy- ses of bert, roberta, distilbert, and xlnet for text-based emotion recognition

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.946798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 292569ae-3a3b-4317-8a27-491341f264c0 · outbound

This paper cites Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-05-11T09:51:00.700331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 619b3639-6816-496d-9ef0-7ebfbbf3de67 · outbound

This paper cites The distress analysis interview corpus of human and computer interviews.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection The distress analysis interview corpus of human and computer interviews

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:50:05.777729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 922fa4ff-7361-4e86-85d0-a5ebd11629f2 · outbound

This paper cites A self-rating depression scale.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection A self-rating depression scale

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.935502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 08b64ddd-4ef7-4f1f-a24b-6ad54a92d2d5 · outbound

This paper cites A rating instrument for anxiety disorders.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection A rating instrument for anxiety disorders

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.958184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e680748e-9202-4b10-8bcc-b6d383f8d0fe · outbound

This paper cites Speech and text foundation models for depression detection: Cross-task and cross-language evaluation.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Speech and text foundation models for depression detection: Cross-task and cross-language evaluation

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.938405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e64d1c24-66b8-4977-8f30-ed4e08c60c82 · outbound

This paper cites Unsupervised instance discriminative learning for depression detection from speech sig- nals.

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection Unsupervised instance discriminative learning for depression detection from speech sig- nals

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T18:45:06.932606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

Observation b537bfb3-a2d6-4cde-a294-3a903e966b27 · inbound