Paper Citation Record · LEDGER

Dynamic Summary Generation for Interpretable Multimodal Depression Detection

As of 10 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 1 inbound Pith citation observation for arXiv:2604.11334.

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

pith.paper-citation-record.v1
2604.11334 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-10T15:42:17.420849Z

measured 33 of 33 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T15:42:17.420849Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-11T10:01:01.142241Z

Reference resolution

32 of 32 outbound references displayed

verified exact4
verified fuzzy26
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 99103ba9-f13b-40c4-8a3d-d0398fe0544a · outbound

This paper cites Dynamic Summary Generation for Interpretable Multimodal Depression Detection.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Dynamic Summary Generation for Interpretable Multimodal Depression Detection

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-05-11T10:01:01.148179Z

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.

Observation f8e228ea-b8a0-4f44-acb4-6bdda0cb59da · outbound

This paper cites The pipeline comprises three stages: binary screening (Stage 1), five-class severity classification (Stage 2), and continuous regression (Stage 3).

Dynamic Summary Generation for Interpretable Multimodal Depression Detection The pipeline comprises three stages: binary screening (Stage 1), five-class severity classification (Stage 2), and continuous regression (Stage 3)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.360492Z

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.

Observation c4350b2e-b429-4fa9-ae55-af5e3e10a55a · outbound

This paper cites The gated features are ˜HT =g T HT , ˜HA = gAHA, ˜HV =g V HV.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection The gated features are ˜HT =g T HT , ˜HA = gAHA, ˜HV =g V HV

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.363765Z

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.

Observation dffaf1ff-77fe-4ad6-947d-6ed0aec3ebf1 · outbound

This paper cites In parallel, we prepend a[CLS]token to Hcat and pass it through a transformer encoder, obtaining a global representationH CLS ∈R d.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection In parallel, we prepend a[CLS]token to Hcat and pass it through a transformer encoder, obtaining a global representationH CLS ∈R d

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.366799Z

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.

Observation a744c11d-7b63-43a5-825a-b4880ed6e7c7 · outbound

This paper cites an unresolved cited work.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-05-17T19:10:07.335825Z

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.

Observation 14cc766e-4f1a-46ce-8384-fbf98f21e475 · outbound

This paper cites T”: text, “A.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection T”: text, “A

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.369516Z

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.

Observation 6950167d-dbe7-4d05-95ab-c3c67f94ba7d · outbound

This paper cites an unresolved cited work.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-05-17T19:10:07.342013Z

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.

Observation 2435f9f2-f489-43ba-8103-64ac390f3ef6 · outbound

This paper cites 20KK0234; by JSPS KAKENHI Grant No.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection 20KK0234; by JSPS KAKENHI Grant No

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.376693Z

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.

Observation d736b791-63f5-4d08-bd93-0e8060b1b8e4 · outbound

This paper cites Ethical approval was not required as confirmed by the license attached with the open access data.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Ethical approval was not required as confirmed by the license attached with the open access data

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.306926Z

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.

Observation 2da156fb-9162-45f2-8492-89e23aa0ffde · outbound

This paper cites Early detection of depression: social network analysis and random forest techniques.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Early detection of depression: social network analysis and random forest techniques

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.303450Z

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.

Observation 33c2dc79-8521-4ab7-8419-ca80d598e0c0 · outbound

This paper cites The heterogeneity of mental health assessment.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection The heterogeneity of mental health assessment

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.310399Z

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.

Observation 823a5749-95db-44e9-aa1d-1e5735b40c64 · outbound

This paper cites Multi-modal adaptive fusion transformer network for the estimation of depres- sion level.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Multi-modal adaptive fusion transformer network for the estimation of depres- sion level

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.323567Z

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.

Observation bc373c28-e60f-4e68-9964-8c12c6461db4 · outbound

This paper cites A sentiment pre- trained text-guided multimodal cross-attention trans- former for improved depression detection.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection A sentiment pre- trained text-guided multimodal cross-attention trans- former for improved depression detection

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.320337Z

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.

Observation 1c35965c-4162-44b6-898c-867938bf53e3 · outbound

This paper cites Enhanced multi- modal depression detection with emotion prompts.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Enhanced multi- modal depression detection with emotion prompts

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.357149Z

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.

Observation 4bba40b8-c838-4955-b671-4490b35d4e7c · outbound

This paper cites The dis- tress analysis interview corpus of human and computer interviews.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection The dis- tress analysis interview corpus of human and computer interviews

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.333080Z

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.

Observation 375287fb-18d4-48a7-975d-21463f3463a7 · outbound

This paper cites Semi-structural interview-based chinese multimodal depression corpus towards automatic preliminary screening of depressive disorders.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Semi-structural interview-based chinese multimodal depression corpus towards automatic preliminary screening of depressive disorders

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.326718Z

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.

Observation c069c794-2ec6-484a-989a-3dc86a910c60 · outbound

This paper cites GPT-4 Technical Report.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection GPT-4 Technical Report

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-05-11T10:01:01.115288Z

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.

Observation 71f521c3-2262-432e-8895-e62818dca732 · outbound

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

Dynamic Summary Generation for Interpretable Multimodal Depression Detection The phq-8 as a measure of current depression in the general population

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.339044Z

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.

Observation c5407c04-255f-4ca7-bb3d-9875448e1fc5 · outbound

This paper cites Health- bench: Evaluating large language models towards im- proved human health.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Health- bench: Evaluating large language models towards im- proved human health

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.294084Z

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.

Observation 3e5879e3-9d0e-4c90-89af-3aafad4f4a01 · outbound

This paper cites Attention is all you need.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Attention is all you need

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.372726Z

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.

Observation b68df614-1ac2-49aa-bf33-e8b3b9e33c93 · outbound

This paper cites Qwen3 embed- ding: Advancing text embedding and reranking through foundation models.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Qwen3 embed- ding: Advancing text embedding and reranking through foundation models

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.329780Z

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.

Observation 3e3b4d59-6b0b-44a2-ac40-73744052ec8b · outbound

This paper cites A concordance correlation coefficient to evaluate reproducibility.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection A concordance correlation coefficient to evaluate reproducibility

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.348027Z

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.

Observation 89092573-91e2-4ae4-9949-437c3f12eb39 · outbound

This paper cites Avec 2019 workshop and challenge: state-of-mind, detect- ing depression with ai, and cross-cultural affect recog- nition.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Avec 2019 workshop and challenge: state-of-mind, detect- ing depression with ai, and cross-cultural affect recog- nition

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.300386Z

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.

Observation 987a4b88-9004-4838-9a37-258f528e36dc · outbound

This paper cites Decoupled Weight Decay Regularization.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Decoupled Weight Decay Regularization

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-05-11T10:01:01.138428Z

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.

Observation 5d26f041-f4c0-4bf0-a092-72c13abb95a9 · outbound

This paper cites Climate and weather: In- specting depression detection via emotion recognition.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Climate and weather: In- specting depression detection via emotion recognition

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.354055Z

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.

Observation 311b6b0f-b352-453d-8096-dc1b396a6295 · outbound

This paper cites Multi-modal and multi-task depression detec- tion with sentiment assistance.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Multi-modal and multi-task depression detec- tion with sentiment assistance

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.351006Z

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.

Observation ac7d493e-643b-4f75-8796-d8ab8e22049b · outbound

This paper cites Tensorformer: A tensor-based multimodal transformer for multimodal sentiment analysis and depression detection.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Tensorformer: A tensor-based multimodal transformer for multimodal sentiment analysis and depression detection

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.316702Z

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.

Observation 267aa127-7983-41d3-a1bc-96692977eab9 · outbound

This paper cites Multimodal senti- ment analysis with mutual information-based disentan- gled representation learning.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Multimodal senti- ment analysis with mutual information-based disentan- gled representation learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.297076Z

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.

Observation 4479f6ea-4116-4b1e-a553-a917bbadf153 · outbound

This paper cites Cubemlp: An mlp- based model for multimodal sentiment analysis and de- pression estimation.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Cubemlp: An mlp- based model for multimodal sentiment analysis and de- pression estimation

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.345004Z

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.

Observation 2c15a3c8-837c-470a-a00c-9b22633885aa · outbound

This paper cites Text-based interpretable depression severity modeling via symptom predictions.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Text-based interpretable depression severity modeling via symptom predictions

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.313417Z

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.

Observation cf60d0e6-5ddc-4889-bb93-c2a3d9e61b08 · outbound

This paper cites Depression Diagnosis and Analysis via Multimodal Multi-order Factor Fusion.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Depression Diagnosis and Analysis via Multimodal Multi-order Factor Fusion

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:01:01.124020Z

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.

Observation bae80adb-83f7-4c20-afa9-bc5103bbea84 · outbound

This paper cites Pie: A personalized information embedded model for text-based depression detection.

Dynamic Summary Generation for Interpretable Multimodal Depression Detection Pie: A personalized information embedded model for text-based depression detection

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T19:10:07.380285Z

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.

Pith citing papers

Observation 99103ba9-f13b-40c4-8a3d-d0398fe0544a · inbound