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Paper Citation Record · LEDGER

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection

As of 14 August 2026, this Paper Citation Record lists 84 of 84 outbound references and 0 inbound Pith citation observations for arXiv:2607.04350.

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

pith.paper-citation-record.v1
2607.04350 v1

Coverage vector

measured 84 of 84 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T19:53:55.129676Z

measured 84 of 84 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

84 of 84 outbound references displayed

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  • unresolved84
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External citation measurements

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Outbound references

Observation 1ad884cf-6ade-44fa-89be-3b6c4d2a0941 · outbound

This paper cites Proceedings of the 60th annual meeting of the association for computational linguistics (volume 1: long papers) , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 60th annual meeting of the association for computational linguistics (volume 1: long papers) , pages=

Reference 1

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Observation 5ff4d658-7ba7-4b47-a9bb-a971d9e1a32a · outbound

This paper cites , title=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection , title=

Reference 2

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:61cc6acb8adde10ccd6472c3e6a47d63786a1450c1416fab7749d7e79b286302

Observation fbf6bc63-1919-4720-b9cc-6273cb39cb8a · outbound

This paper cites Expert Systems with Applications , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Expert Systems with Applications , volume=

Reference 3

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:96bd59f532f98def67cabb1a01d8190de20f8b4302929e71c9b6998a160ad6aa

Observation 8a33592d-c732-4783-acb9-a76c07db3bb4 · outbound

This paper cites Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence,.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence,

Reference 4

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:9d70b6dc4615c9b28ccaed04dd36472c5306a7afd846795a3a9cd7a518e7c66e

Observation fec3c129-07ba-46fa-a45a-16d60d1d6eee · outbound

This paper cites European Conference on Information Retrieval , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection European Conference on Information Retrieval , pages=

Reference 5

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:a7fa8ef33105e85ac74fcfd4b2b2d74952d7380d859c0fdd11daca037d0ad343

Observation 4783f787-2e60-46a8-8f2f-68c9dd5b18b4 · outbound

This paper cites Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) , pages=

Reference 6

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:e407765c3032d3a2aa1cf8f1580ce216fc527d0629e33235c2513975b0300288

Observation f6894681-a1c1-47e8-877b-116a290caddf · outbound

This paper cites Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers) , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers) , pages=

Reference 7

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:e5507ed20aafb1b4320ff5fa488bb0c8750bff4da3697d1abfe88e6101e34ffb

Observation f7750697-f4dd-4302-9f5c-c85b39dbd92c · outbound

This paper cites Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing: Industry Track , pages=

Reference 8

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Observation ebeb0f2b-8abe-4ab9-bcc9-9dc16adefef4 · outbound

This paper cites Proceedings of the 9th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2024) , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 9th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2024) , pages=

Reference 9

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:c4df3c5c78ea65e5143e3c173996323a9f2ac1f5b2953ed7eb16bffd08613227

Observation d48e76cf-3564-4540-a7a1-40cbd211b112 · outbound

This paper cites Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 10

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:0b90340ac4e7fdf96f609513c8f58582e3fdfe3a452247d3f7408213fc5b2b08

Observation 572074e8-9a45-4226-8bd2-82e464493296 · outbound

This paper cites proceedings of the 44th international ACM SIGIR conference on research and development in information retrieval , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection proceedings of the 44th international ACM SIGIR conference on research and development in information retrieval , pages=

Reference 11

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Observation 530ab92c-f8ee-4f12-a08e-6e9719b37717 · outbound

This paper cites Proceedings of the international AAAI conference on web and social media , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the international AAAI conference on web and social media , volume=

Reference 12

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:fd4c76f8e0db648a4b2eeb6beab08fda8145daf034b9d2dbce561dcfe054c79b

Observation 7c2bb238-12cf-4a1a-8033-963a6490b98a · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 13

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:5145421573c154ef61b5c88dabf0b068d5d35c166c9a4a2ed8e1d4d8a32d4b35

Observation 7c3a3fe8-8628-4388-8068-8ddeae6952a4 · outbound

This paper cites Neural networks , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Neural networks , volume=

Reference 14

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:c313092ac6b5d9235d1c4852750fd7f59dd03cf6c14c48b69109754aea85378d

Observation 76a3a4ae-d410-4aaf-9df2-29945c3b1424 · outbound

This paper cites Proceedings of the AAAI conference on artificial intelligence , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the AAAI conference on artificial intelligence , volume=

Reference 15

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:a6a6b02689c957fa8739c19fc55c6371bbd9b0dda405219ae9c734712c751fbe

Observation 259e77d7-dab4-41aa-89a2-073b8056c43d · outbound

This paper cites Information Sciences , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Information Sciences , volume=

Reference 16

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:8d1aa671cfef999f67a36451dd855a5cbb8170bd6eb13d97e293417c361277a1

Observation 1c43b84d-e7b7-4915-9ca8-9c66a07b045c · outbound

This paper cites PLoS medicine , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection PLoS medicine , volume=

Reference 17

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:418ef2eb8bb893d0229ecf40eb34252280b125ecb2f2cb085e85066b4b9c0fd7

Observation 94647da8-8d6b-4db5-a5b5-1977ab0c82cd · outbound

This paper cites an unresolved cited work.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Unresolved cited work

Reference 18

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:166e7c85c2558e9d9832e92c09c407c1c6079166f3f85fc673840aaa82c8efcc

Observation a6719608-f821-4e28-bd54-5c78ed84d9b4 · outbound

This paper cites 2025 , month = aug, url =.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection 2025 , month = aug, url =

Reference 19

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Observation a630da77-a655-4aaa-8cb5-72113930b675 · outbound

This paper cites Neural computation , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Neural computation , volume=

Reference 20

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:b5866bb456509418e96e1a76965fa0d8ce5a1f0dfe31c8330d344245a28872b1

Observation 98fda0bf-99b7-43b1-af02-b42596c95a8e · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 21

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Observation 2b15b5bb-6014-4747-b0aa-bc3875c4b6d8 · outbound

This paper cites IEEE Latin America Transactions , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection IEEE Latin America Transactions , volume=

Reference 22

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:cf2d16ef8ddf5d9a2cb14f5447677156ee28781bc264ce0ace3a024d47544393

Observation 2f099b97-9f5d-46c1-8b33-47a02b6b2dee · outbound

This paper cites IEEE Access , year=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection IEEE Access , year=

Reference 23

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:797934f434ea3079e80d3c00e544a3feb4863353e28717b4fe5b34c5b8d128ee

Observation c5230d94-7db1-42d5-94b4-d3ea08afe70e · outbound

This paper cites Proceedings of the 2017 conference on empirical methods in natural language processing , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 2017 conference on empirical methods in natural language processing , pages=

Reference 24

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Observation 9cd56ea7-246b-41cf-8c6d-585ec917c0f8 · outbound

This paper cites Proceedings of the 32nd Pacific Asia conference on language, information and computation , year=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 32nd Pacific Asia conference on language, information and computation , year=

Reference 25

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:aed60a868ac9337f0180c29230f6531da8e6254ccf3126a7882b9978ad723959

Observation 82517e54-e58a-4261-94bb-6b4785b45d35 · outbound

This paper cites Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 26

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Observation 24468e8f-aafa-475b-b5e3-c83fc0bccdcc · outbound

This paper cites Findings of the Association for Computational Linguistics: ACL 2025 , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Findings of the Association for Computational Linguistics: ACL 2025 , pages=

Reference 27

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Observation 16dbdec4-b3bf-45d9-acfd-d39a009b5b42 · outbound

This paper cites Journal of Machine Learning Research , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Journal of Machine Learning Research , volume=

Reference 28

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Observation 49b1d5a7-449a-440e-b834-614bd41f274d · outbound

This paper cites Unifying distillation and privileged information.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Unifying distillation and privileged information

Reference 29

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Observation 0d3a7263-e7ef-4b59-928d-8c216dd47005 · outbound

This paper cites Proceedings of the workshop on computational linguistics and clinical psychology: From linguistic signal to clinical reality , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the workshop on computational linguistics and clinical psychology: From linguistic signal to clinical reality , pages=

Reference 30

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Observation 41cc7c0b-c426-4450-b723-5b4f11fec73a · outbound

This paper cites Proceedings of the 2nd workshop on computational linguistics and clinical psychology: from linguistic signal to clinical reality , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 2nd workshop on computational linguistics and clinical psychology: from linguistic signal to clinical reality , pages=

Reference 31

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Observation 1f5a2179-e8a3-49e1-a84a-4a3aa5ac44c8 · outbound

This paper cites Proceedings of the international AAAI conference on web and social media , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the international AAAI conference on web and social media , volume=

Reference 32

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:a285085d4cbf9cc0370b7646a43e75256a10b54bc245e33c98e9a4b91896c757

Observation eb70cdb8-f20a-4e1c-9e5d-2976a660fe86 · outbound

This paper cites Sensitive Self-disclosures, Responses, and Social Support on Instagram: The Case of.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Sensitive Self-disclosures, Responses, and Social Support on Instagram: The Case of

Reference 33

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Observation 5a777fa4-3f23-4a05-a687-17b33225be17 · outbound

This paper cites Proceedings of the 2018 EMNLP workshop SMM4H: the 3rd social media mining for health applications workshop & shared task , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 2018 EMNLP workshop SMM4H: the 3rd social media mining for health applications workshop & shared task , pages=

Reference 34

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Observation 432aa3f4-a6a1-48b7-85bd-56dbfb3b023d · outbound

This paper cites Proceedings of the fifth workshop on computational linguistics and clinical psychology: from keyboard to clinic , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the fifth workshop on computational linguistics and clinical psychology: from keyboard to clinic , pages=

Reference 35

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Observation f7f344e3-5fda-4d27-8f7f-d5a2c1c7b2e6 · outbound

This paper cites Proceedings of the fourth workshop on computational linguistics and clinical psychology—from linguistic signal to clinical reality , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the fourth workshop on computational linguistics and clinical psychology—from linguistic signal to clinical reality , pages=

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:7e14f373e29d68afb4cff5d9f495491aae6ed584d76775a975f87da6dbb453a3

Observation 424d3246-1007-49c7-8331-8684f5e75eef · outbound

This paper cites Proceedings of the Fifth Workshop on Computational Linguistics and Clinical Psychology: From Keyboard to Clinic , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the Fifth Workshop on Computational Linguistics and Clinical Psychology: From Keyboard to Clinic , pages=

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:16b5e2196531ef31b615d8254d704f76f225ae345fbcbcffc634cbb8ef8eb6d6

Observation dcf76edc-f716-4b69-8863-dcd6a7740d15 · outbound

This paper cites Proceedings of the 28th international conference on computational linguistics , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 28th international conference on computational linguistics , pages=

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:51ddf98cf3e433af7fb592093791d17942ccd76ddda7dc09314fb95922999b51

Observation 0750722a-a7ae-4a38-999c-ea1b0912959a · outbound

This paper cites NPJ digital medicine , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection NPJ digital medicine , volume=

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:4f4a6d0468956c35cc0cd35387bfa153d60cff213ec0914ebdd1c29d09c4be50

Observation d061d52f-2bcd-48dc-9e0f-cc2e6a4eaedb · outbound

This paper cites Proceedings of the 11th international workshop on health text mining and information analysis , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 11th international workshop on health text mining and information analysis , pages=

Reference 40

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:1b751023302b7581301cf7cef175641b1b4d60b704ee569f6a44bd2d06f28aeb

Observation 2ed34260-2887-4fcd-9079-7316d8a88772 · outbound

This paper cites Proceedings of the tenth international workshop on health text mining and information analysis (LOUHI 2019) , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the tenth international workshop on health text mining and information analysis (LOUHI 2019) , pages=

Reference 41

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:0a8f409f0eb5aa4eb6cc1428eccf7f9041381182f7fb430b069b4ff74e779dab

Observation b0b1be7e-4fb1-45c2-b702-4324dae1db5f · outbound

This paper cites Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) , pages=

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:1ae4ed0884887232a548c5f8b846061ca82cd718a1040bf6eb0b656169fb5591

Observation a1e080fb-b9f6-4ab1-8227-49b99ecae454 · outbound

This paper cites Computational Linguistics , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Computational Linguistics , volume=

Reference 43

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:395ad340031b6b2f8a73ec3aa94dc1e9f5cf64026d9b9084e31a978d23cb55be

Observation 56784b8e-4c48-461e-993c-3958331a74b5 · outbound

This paper cites Journal of medical Internet research , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Journal of medical Internet research , volume=

Reference 44

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:0cd270775c55ee29cd0fe9bde10f03d6b725bb50ebc04958e736034207568f7a

Observation 4bbb0de6-5b6d-4f14-8562-f62e64f80a6d · outbound

This paper cites Proceedings of the 10th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2025) , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 10th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2025) , pages=

Reference 45

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:4fe3eb6b2c06e05cbc3663b2227b716b4ef94e0119d0e51399eb0702e930ce28

Observation 836da573-9aab-4899-b18c-1cd0ded22619 · outbound

This paper cites Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 46

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:a8e3f18502342caf97c42b60c0c31a5eb9575593e7b1f7d26ab301562fd7c3ac

Observation 512bfe05-5f37-4297-a437-d5aff52a42bc · outbound

This paper cites Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) , pages=

Reference 47

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:97a4f46a0113a635c783980656170c0331ed3af9052cfeeb90cef232501fc4ed

Observation 1e723a5c-ec16-4ccf-ae55-21e96150a136 · outbound

This paper cites Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining , pages=

Reference 48

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:73d560b5a021223eafa18c75b444063b955ce3763e0b1e6c5c47190a0b85980a

Observation e4dfdab3-e2c1-4dad-9341-133d638c8895 · outbound

This paper cites Neural Networks , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Neural Networks , volume=

Reference 49

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:bf7a2e9bd7b4f13423d357203e71f29d7b505e47f50b45f657fab338c2a234f1

Observation 78f2162a-4acc-44c1-b97c-c5708a85b642 · outbound

This paper cites and Williams, Janet B.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection and Williams, Janet B

Reference 50

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:8f7db72bb059b6c9897f2e38b91e43cf0d5f63bc1e40ec8c98f398b4c0196713

Observation 19776494-de93-44b0-b5f3-21f80239a287 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Advances in Neural Information Processing Systems , volume=

Reference 51

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:4d7f6672bacc2258bcca6d7a72de0f1be02e69e4be08465ee90ecb69a6121e26

Observation 7e35a5e8-bdd5-4a4e-93f2-b0a5f2d9bb3c · outbound

This paper cites Proceedings of the 9th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2024) , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 9th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2024) , pages=

Reference 52

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:c065227b01380b0131c73a80c5bb8de248ca201888d4492d55236659d944ff02

Observation 19907ae7-ffd3-4cd3-a5d8-55c7d8436c30 · outbound

This paper cites and Jackson, Thomas W.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection and Jackson, Thomas W

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:2f90f9156d13b74f7b943c608943eb84363252b940a316c341b0ebecb1cca8a8

Observation a917ac34-5e40-4b11-8cc2-a95953e6e1a0 · outbound

This paper cites Proceedings of the 2nd workshop on computational linguistics and clinical psychology: from linguistic signal to clinical reality , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 2nd workshop on computational linguistics and clinical psychology: from linguistic signal to clinical reality , pages=

Reference 54

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:ecf2c499606a863926f78664e1cde256a5f9a8574eec819a094b9160284ae6e1

Observation 7133ae29-c5c7-4698-83d0-00ad477e373c · outbound

This paper cites Proceedings of the National Academy of Sciences , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the National Academy of Sciences , volume=

Reference 55

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:dcfb4bbe65edcc0c4b6db3e201785ee3c637a9ff0ddc12a41e5b2211e85d625c

Observation e42b23f3-79b1-4b7e-83c8-cb7b090133fd · outbound

This paper cites Current Opinion in Behavioral Sciences , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Current Opinion in Behavioral Sciences , volume=

Reference 56

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:0c5af810a87655434982476c39ac05d1af23bc050ce7f518bb47b2519396a091

Observation f29cf947-89dd-4fda-be06-9cd9fdde4471 · outbound

This paper cites Proceedings of the Eighth Workshop on Computational Linguistics and Clinical Psychology , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the Eighth Workshop on Computational Linguistics and Clinical Psychology , pages=

Reference 57

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:20bcbdfe8907c2f8ab8157cf9e3004bf5c93a579b818d6dd40df732d6d219516

Observation 43ef268b-263a-4c8f-ba47-ad87193c3a46 · outbound

This paper cites JMIR AI , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection JMIR AI , volume=

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:5ffd60fa7db52c04be82dbf6e033d95366aca292df7a30813031dbc52453a78a

Observation 1fd4a915-435e-4928-8017-45f6e03846c4 · outbound

This paper cites EPJ Data Science , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection EPJ Data Science , volume=

Reference 59

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:70105d777cb6075b8988e2be32c9e89bfb96788d58f88b3cdaf55add8245563e

Observation 998a425f-712d-4177-940c-e0bf929f9340 · outbound

This paper cites IEEE transactions on knowledge and data engineering , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection IEEE transactions on knowledge and data engineering , volume=

Reference 60

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:adfd4a5ae8b3b2fc2beadba0156014e36be6605cb7fb0c40e3831fcca3d3c68a

Observation 6487e55a-1027-4afc-b053-a0a70aa2c959 · outbound

This paper cites Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) , pages=

Reference 61

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:c54b7069e631dcac3138567d2843d164e711af44280aa01b39b1298f168b8e91

Observation 2f987075-e468-4b5a-a79a-c93e372a2080 · outbound

This paper cites JMIR mental health , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection JMIR mental health , volume=

Reference 62

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:eff468b25a4236dfef0cb1282c8c92f5b87b5bcdd3c03ccbad9651ea4748c8ec

Observation 23ed071b-5979-4d00-9c81-c2da292fadec · outbound

This paper cites Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 63

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:d61018a15f0dcf53dde18e52a2e54510ce49723eef4dacc1363528980d74715c

Observation 00fff755-3fdc-4f51-9fce-3715c3d4e1f0 · outbound

This paper cites 2019 , address=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection 2019 , address=

Reference 64

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:dba2f980a22348009ce9316c422ef42137e00b18abd30a9f88841f38c45ded54

Observation 58e4e644-fb4a-4f72-818e-2be2c9af8fb7 · outbound

This paper cites an unresolved cited work.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Unresolved cited work

Reference 65

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:a263f51899e5b62e719ca5d6241e445e3f16e53b3f8158c0d1183597dd5137c2

Observation 9cfbccdc-1725-412c-b0a4-cc2a5f1cc9c8 · outbound

This paper cites 2026 , eprint=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection 2026 , eprint=

Reference 66

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:f252f06f801ee0c92338f17500f3ca23f5f487f6c3545e3039614e81ce872bc1

Observation a8d2b19b-7bcc-4697-83b0-635b1e615647 · outbound

This paper cites Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) , pages=

Reference 67

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:6ed5f050fabab13ec8696d38af54839100250a480ea1dc400abe7b23c2e701e5

Observation 07bba4b4-e406-46f4-9390-abeadfe6a79a · outbound

This paper cites Proceedings of the 31st International Conference on Computational Linguistics , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 31st International Conference on Computational Linguistics , pages=

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:f9737efeab407d08f67c944fc5e758dca394baf592b2141f016870eb1b1351bc

Observation 71ab8c72-559e-4f3c-bb77-6a70d3e5faf3 · outbound

This paper cites Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 69

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:0fe5c1576125bf48d56f13f18096da2ce76b4d82b16a009184fb340aedb5b3cc

Observation 72772cff-d55c-434d-9e45-d1552ccb5616 · outbound

This paper cites IEEE Transactions on Neural Networks and Learning Systems , year=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection IEEE Transactions on Neural Networks and Learning Systems , year=

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:327d5d0a568cd7dec2dd7b6c333c8c6046e4986087048ccbc737f5926f11a541

Observation f2ecdf8b-d42f-4e89-9eda-2fdaf7ff161b · outbound

This paper cites Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

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source=arxiv_source observed=2026-07-11T19:53:55.129676Z digest=sha256:24802ffb79dc58ca311116df847d70dd982d93384dd1229e19fbffc6f341d94a

Observation ceaeddc3-603f-4356-96ac-89551be19351 · outbound

This paper cites Findings of the Association for Computational Linguistics: EMNLP 2020 , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Findings of the Association for Computational Linguistics: EMNLP 2020 , pages=

Reference 72

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Observation 455f951c-77fd-4d13-8f3d-2096a9652808 · outbound

This paper cites Proceedings of the 2018 conference on empirical methods in natural language processing , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 2018 conference on empirical methods in natural language processing , pages=

Reference 73

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Observation e5961275-dc0d-4102-8d4f-191feb513be1 · outbound

This paper cites Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers , pages=

Reference 74

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Observation ca7c8bef-6345-4931-aed5-ac63e5c9aed3 · outbound

This paper cites Proceedings of the ACM Web Conference 2023 , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Proceedings of the ACM Web Conference 2023 , pages=

Reference 75

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Observation 03faacce-064f-44e8-ab71-6cb4853e167e · outbound

This paper cites Findings of the Association for Computational Linguistics: ACL 2024 , pages=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Findings of the Association for Computational Linguistics: ACL 2024 , pages=

Reference 76

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Observation 94f48101-0ce6-4ca2-85b1-ccf42a8bda18 · outbound

This paper cites A Gold Standard Dataset and Evaluation Framework for Depression Detection and Explanation in Social Media using LLMs.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection A Gold Standard Dataset and Evaluation Framework for Depression Detection and Explanation in Social Media using LLMs

Reference 77

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Observation 3a5c4157-5739-4fd5-8c9b-e4ea44ab5941 · outbound

This paper cites Generating Medically-Informed Explanations for Depression Detection using LLMs.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Generating Medically-Informed Explanations for Depression Detection using LLMs

Reference 78

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Observation 7e6ce770-9e90-4d25-a020-e6a520943d5b · outbound

This paper cites Interpretable Depression Detection from Social Media Text Using LLM-Derived Embeddings.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Interpretable Depression Detection from Social Media Text Using LLM-Derived Embeddings

Reference 79

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Observation d458fab5-409e-4aa5-9a8b-e32370902bb2 · outbound

This paper cites CNSocialDepress: A Chinese Social Media Dataset for Depression Risk Detection and Structured Analysis.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection CNSocialDepress: A Chinese Social Media Dataset for Depression Risk Detection and Structured Analysis

Reference 80

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Observation ea9c75d0-645f-453d-a587-3f1411b6b2a6 · outbound

This paper cites Overview of the.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Overview of the

Reference 81

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Observation 851dee28-7680-4dab-9981-c586704f4b66 · outbound

This paper cites 2026 , eprint=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection 2026 , eprint=

Reference 82

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Observation 403a0d32-6e73-407f-a39a-1d423e1828e4 · outbound

This paper cites an unresolved cited work.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection Unresolved cited work

Reference 83

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Observation 98c54e3f-d6b7-4dd5-b94a-2b0de862b7bf · outbound

This paper cites JMIR Infodemiology , volume=.

WPG-MoE: Weak-Prior-Guided Dense Mixture-of-Experts for User-Level Social Media Depression Detection JMIR Infodemiology , volume=

Reference 84

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Pith citing papers

No inbound Pith citation observations are available.