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Paper Citation Record · LEDGER

Bandwidth Selection in Kernel Density Estimation for Model Calibration

As of 8 August 2026, this Paper Citation Record lists 100 of 115 outbound references and 0 inbound Pith citation observations for arXiv:2606.29925.

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

pith.paper-citation-record.v1
2606.29925 v1

Coverage vector

measured 100 of 115 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T07:48:52.228289Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

100 of 115 outbound references displayed

  • verified exact5
  • verified fuzzy0
  • unresolved93
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 64943627-fca2-48bc-82ae-6a31af3a0d20 · outbound

This paper cites 1999 , publisher=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration 1999 , publisher=

Reference 1

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Observation 2c896841-7991-43d9-9115-f4ad8e4da8b2 · outbound

This paper cites Advances in neural information processing systems , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Advances in neural information processing systems , volume=

Reference 2

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Observation 25056816-5028-4c93-8ea2-a7bb2819e0c1 · outbound

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

Bandwidth Selection in Kernel Density Estimation for Model Calibration Proceedings of the AAAI conference on artificial intelligence , volume=

Reference 3

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Observation da77312d-dfe5-4dad-b472-76428f99b743 · outbound

This paper cites Transactions on Machine Learning Research , year=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Transactions on Machine Learning Research , year=

Reference 4

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Observation 9f724066-baae-46ee-a327-21743fa4047c · outbound

This paper cites 1999 , publisher=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration 1999 , publisher=

Reference 5

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Observation 4c846c9a-a3a1-4a11-9730-de39bee2ac5d · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops , pages=

Reference 6

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Observation b13a6d9d-9cb1-48f3-b987-0b0c91e83f72 · outbound

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

Bandwidth Selection in Kernel Density Estimation for Model Calibration The Journal of Machine Learning Research , volume=

Reference 7

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Observation 5b2cf4de-b920-4c47-8d31-ac4c26572dd0 · outbound

This paper cites The 22nd international conference on artificial intelligence and statistics , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration The 22nd international conference on artificial intelligence and statistics , pages=

Reference 8

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Observation 4428a9be-a7df-4839-8acc-66e3db242031 · outbound

This paper cites International Conference on Learning Representations , year=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration International Conference on Learning Representations , year=

Reference 9

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Observation 653c7895-c434-43b9-aade-825ad70c03cd · outbound

This paper cites The Eleventh International Conference on Learning Representations , year=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration The Eleventh International Conference on Learning Representations , year=

Reference 10

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Observation e7b4b712-f9c5-4b4f-8e96-d89a19f7075e · outbound

This paper cites 2024 , publisher =.

Bandwidth Selection in Kernel Density Estimation for Model Calibration 2024 , publisher =

Reference 11

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Observation 48a4fb99-0317-45c3-b935-c337f0cac967 · outbound

This paper cites Proceedings of the IEEE/CVF international conference on computer vision , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Proceedings of the IEEE/CVF international conference on computer vision , pages=

Reference 12

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Observation eaf39f9e-c9e4-4de7-a371-f29cbd530a6a · outbound

This paper cites Computer Vision--ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11--14, 2016, Proceedings, Part IV 14 , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Computer Vision--ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11--14, 2016, Proceedings, Part IV 14 , pages=

Reference 13

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Observation 350b86c4-c3d3-402d-a992-d2fe99b92efa · outbound

This paper cites Proceedings of the IEEE conference on computer vision and pattern recognition , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Proceedings of the IEEE conference on computer vision and pattern recognition , pages=

Reference 14

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Observation 3c281dd8-754f-490c-b505-539027ae38c3 · outbound

This paper cites arXiv e-prints , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration arXiv e-prints , pages=

Reference 15

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Observation 1b5c4f79-24b5-473b-ba76-b7abb3bbd325 · outbound

This paper cites GPT-4 Technical Report.

Bandwidth Selection in Kernel Density Estimation for Model Calibration GPT-4 Technical Report

Reference 16

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Observation 03b94d7c-0e9d-4b66-912c-3269103f31a3 · outbound

This paper cites European Journal of Cancer , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration European Journal of Cancer , volume=

Reference 17

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Observation bd34905d-8aa8-4784-9312-62e8c5b23596 · outbound

This paper cites International Conference on Learning Representations , year=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration International Conference on Learning Representations , year=

Reference 18

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Observation 662c2862-e390-48e5-a587-e78ff5e8d178 · outbound

This paper cites 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA) , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA) , pages=

Reference 19

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Observation 126d9d65-5cbd-4adf-b761-0ca42384f047 · outbound

This paper cites Advances in neural information processing systems , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Advances in neural information processing systems , volume=

Reference 20

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Observation ca966636-fbb2-4cea-8dd6-b8bc846551a5 · outbound

This paper cites International Conference on Learning Representations, Virtual conference, May 3-May 7, 2021 , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration International Conference on Learning Representations, Virtual conference, May 3-May 7, 2021 , pages=

Reference 21

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Observation 1b704456-bfd6-43c6-8674-c86344507682 · outbound

This paper cites Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages=

Reference 22

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Observation bb8b64fb-8c0d-4901-8ff5-afff005ecc5d · outbound

This paper cites Advances in neural information processing systems , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Advances in neural information processing systems , volume=

Reference 23

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Observation c442bc76-53c8-4813-83be-4cc88496e515 · outbound

This paper cites Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part I 15 , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part I 15 , pages=

Reference 24

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Observation b2202a7d-f498-4053-af8f-aca3f22a9421 · outbound

This paper cites Reliability, Sufficiency, and the Decomposition of Proper Scores , journal =.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Reliability, Sufficiency, and the Decomposition of Proper Scores , journal =

Reference 25

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Observation 8b653689-989c-4090-861a-febeee635345 · outbound

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

Bandwidth Selection in Kernel Density Estimation for Model Calibration Advances in Neural Information Processing Systems , volume=

Reference 26

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Observation 98f41673-9ac3-4972-af8f-8740417330cd · outbound

This paper cites Pattern Recognition Letters , year=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Pattern Recognition Letters , year=

Reference 27

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Observation 06d0cb69-df45-48f5-8933-2b73fe584813 · outbound

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Bandwidth Selection in Kernel Density Estimation for Model Calibration , author=

Reference 28

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Observation 2bd532ef-5cb0-405b-8f50-e28e06347abc · outbound

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Bandwidth Selection in Kernel Density Estimation for Model Calibration International Conference on Machine Learning , YEAR =

Reference 29

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Observation efa5340d-ee66-4c53-b048-c9b09461bbe0 · outbound

This paper cites International conference on machine learning , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration International conference on machine learning , pages=

Reference 30

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Observation 099902e2-343c-437d-801e-ae0e27f76d79 · outbound

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Bandwidth Selection in Kernel Density Estimation for Model Calibration 2009 , author =

Reference 31

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Observation 09edf256-a456-48f2-b089-36257048027e · outbound

This paper cites doi: https://doi.org/10.1016/0041-5553(67)90040-7.

Bandwidth Selection in Kernel Density Estimation for Model Calibration doi: https://doi.org/10.1016/0041-5553(67)90040-7

Reference 32

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Source-reported events for the cited work

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Bandwidth Selection in Kernel Density Estimation for Model Calibration GitHub repository , doi =

Reference 33

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Observation 273d0222-4c1e-4e1a-9fa3-d9175da45b54 · outbound

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Bandwidth Selection in Kernel Density Estimation for Model Calibration Ovcharov , title =

Reference 34

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Observation 87465498-fdce-4dd5-8c84-448e2519d0cf · outbound

This paper cites Better Uncertainty Calibration via Proper Scores for Classification and Beyond , volume =.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Better Uncertainty Calibration via Proper Scores for Classification and Beyond , volume =

Reference 35

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Bandwidth Selection in Kernel Density Estimation for Model Calibration Advances in Neural Information Processing Systems , volume=

Reference 36

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Observation 41be9db8-7f20-4757-adc0-64bafb266508 · outbound

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Bandwidth Selection in Kernel Density Estimation for Model Calibration Journal of Multivariate Analysis , volume=

Reference 37

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Observation a8721f68-1b0a-458a-b452-88f489ecd12e · outbound

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Bandwidth Selection in Kernel Density Estimation for Model Calibration Procedings of the British Machine Vision Conference 2016 , pages=

Reference 38

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Observation 471bfc3a-a4db-4866-9a4f-796e434c5802 · outbound

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Bandwidth Selection in Kernel Density Estimation for Model Calibration Nature Medicine , volume=

Reference 39

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Observation 99ef4493-b540-44dc-b119-21e9d83886bd · outbound

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

Bandwidth Selection in Kernel Density Estimation for Model Calibration Advances in Neural Information Processing Systems , volume=

Reference 40

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Observation e05c0809-a871-4ebe-a567-7eb76bbf687d · outbound

This paper cites Proceedings of the 35th International Conference on Machine Learning , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Proceedings of the 35th International Conference on Machine Learning , pages=

Reference 41

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Observation 9799e09b-746b-4150-a029-f6081d67bbad · outbound

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

Bandwidth Selection in Kernel Density Estimation for Model Calibration Advances in Neural Information Processing Systems , volume=

Reference 42

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Observation 458cff6e-2ca5-451d-b3f7-a5663c26ba7a · outbound

This paper cites Transactions on Machine Learning Research , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Transactions on Machine Learning Research , pages=

Reference 43

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Observation cad91d66-f149-43e4-b64c-f74690d3e906 · outbound

This paper cites The Ninth International Conference on Learning Representations (ICLR 2021) , year=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration The Ninth International Conference on Learning Representations (ICLR 2021) , year=

Reference 44

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Observation 96b3be6e-6435-4223-ba0e-2cb2fc99a76c · outbound

This paper cites International Conference on Machine Learning , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration International Conference on Machine Learning , pages=

Reference 45

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:a889da4db7e02c2454e121e4013d684e36da61427bd5081fcbce8e65d380e6c2

Observation 8523c8df-b417-47e8-a684-af895a04e221 · outbound

This paper cites Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=

Reference 46

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:97b116e8370f27015862fe9487aa956951d506cf8864a16399dbc8f4efce0291

Observation ae8c995e-82df-41cf-9aca-4a202b08f506 · outbound

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

Bandwidth Selection in Kernel Density Estimation for Model Calibration Advances in Neural Information Processing Systems , volume=

Reference 47

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:bfab93e9f312e4ce54b85800e5f31108adf1f38a1aad122b35fe5638291bf651

Observation 3dd26aff-59ba-408a-8e8a-fa1805d3ab8c · outbound

This paper cites Nature Medicine , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Nature Medicine , volume=

Reference 48

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:535bbf48635610813d87ec592c50cf8277f3ddbb022c4c9ae274e9aa7a638491

Observation c3273a88-68b6-4ed6-8e2f-3b2e3629efde · outbound

This paper cites The Lancet Digital Health , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration The Lancet Digital Health , volume=

Reference 49

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:8c7c269b462f291044011d04286c661ebd7d304a324f54dde77a9d1bc8e43e64

Observation c68d97d8-14c4-4609-8b07-3dc2e6e06cdc · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 50

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local_arxiv, observed 2026-06-30T07:54:22.238055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:85f4ebaaf8c5eeb446370b45b1d581ee34c4fe497f939a8e10a8c9dfa373e468

Observation f64f39e6-89ec-4bcd-b7f8-354136577a24 · outbound

This paper cites Journal of Applied Meteorology and Climatology , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Journal of Applied Meteorology and Climatology , volume=

Reference 51

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:108c057b09d024603d9478cc51c443417e601ee0158f99eeb0911c1f30ec0f82

Observation c7a9d64e-c0e7-483d-9da0-559f0d61063d · outbound

This paper cites Proceedings of the IEEE conference on computer vision and pattern recognition , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Proceedings of the IEEE conference on computer vision and pattern recognition , pages=

Reference 52

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Observation 48ce2b36-26d4-4af5-8286-c2accb9aa04d · outbound

This paper cites 2009 IEEE conference on computer vision and pattern recognition , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration 2009 IEEE conference on computer vision and pattern recognition , pages=

Reference 53

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:0b88eb77a7568ac4e5a78d0b0db31aa20ecfd08e5611dbd1def08b62b3b92266

Observation eca64423-5c16-42f0-9e5a-67d1f0dea7e0 · outbound

This paper cites A Novel Characterization of the Population Area Under the Risk Coverage Curve (AURC) and Rates of Finite Sample Estimators.

Bandwidth Selection in Kernel Density Estimation for Model Calibration A Novel Characterization of the Population Area Under the Risk Coverage Curve (AURC) and Rates of Finite Sample Estimators

Reference 54

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verified exact
arxiv_id, observed 2026-06-30T07:54:22.241339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:7033257bd886af18bf5f4f92a53fc1c9698c73c98090647254636f8e7dac45f6

Observation d1202a43-433c-4405-9647-0ed8b1ddf52f · outbound

This paper cites What classifiers know what they don't?.

Bandwidth Selection in Kernel Density Estimation for Model Calibration What classifiers know what they don't?

Reference 55

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arxiv_id, observed 2026-06-30T07:54:22.244910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:573646f771d5efefcdde35f711e72a8b63ac8898815e5a80a582858d56302222

Observation d51ce57e-ec17-40de-b1c6-66eb1a9686c6 · outbound

This paper cites Statistics , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Statistics , volume=

Reference 56

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:50f42b0a1e2ffade757364c8e8fd4d6d769a0444be01145858e546c431a5c35e

Observation 0b5ad9da-c5e2-404e-af11-9acf60978df2 · outbound

This paper cites International Conference on Artificial Intelligence and Statistics , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration International Conference on Artificial Intelligence and Statistics , pages=

Reference 57

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:f545260ad0fdb98c2bcfac08581fe995f8dd641b9ecffd0704730b75bba0eb4c

Observation 23f34c0b-5929-44bf-9772-1ec585ec79e8 · outbound

This paper cites Master's thesis, University of Tront , year=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Master's thesis, University of Tront , year=

Reference 58

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:56ca5c9f0c08e63ea935cbc01c1cfe5f69c7870c80b752c306499b6236508c5d

Observation 1cd81338-ce48-4d1d-919b-a1718fad26ff · outbound

This paper cites Statistics and Computing , year=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Statistics and Computing , year=

Reference 59

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:5f315c55f5760246aef9c3a96a3e0ec1734a6e03d624a7b42d551d8e2d35762b

Observation 2379a626-9aad-4bec-98f5-4eeae6e7b482 · outbound

This paper cites 1994 , publisher=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration 1994 , publisher=

Reference 60

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:0f302d5c20e71d32ebefef0c78abae097edd22a85ffdb5d3eb18ddc87083c10e

Observation 56ee20c4-b23b-47a6-b99a-5bcbd831f408 · outbound

This paper cites 1987 , publisher=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration 1987 , publisher=

Reference 61

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:9e98f3af5f33365fd1590d3738f96cc8ee73cd54526a70a6f06eba516f261852

Observation 3b10731c-0e1e-4d73-b776-3acc12549a70 · outbound

This paper cites 5th International Conference on Learning Representations , year=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration 5th International Conference on Learning Representations , year=

Reference 62

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:b10a7e146b70d7bc5d0b47086d6ca2b797561210826c2975d1df226da41f9a44

Observation 9aef4fbe-e83a-407c-b7f0-9853bd28565b · outbound

This paper cites IEEE Transactions on information theory , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration IEEE Transactions on information theory , volume=

Reference 63

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:aaf85b8097f2eb30abb5c7ea9c94d8d58fcc48dd7e979399ae76275eac1d8fe2

Observation 0685505c-5e8f-4e58-a04f-26d820571e48 · outbound

This paper cites 1965 , publisher=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration 1965 , publisher=

Reference 64

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:1bcf64277024ea2fa4d83965b415a5a7dd0991c615369827108c17609528195e

Observation 2a77fdce-8e49-42b5-b5b2-3b83ce283d47 · outbound

This paper cites Journal of the American statistical Association , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Journal of the American statistical Association , volume=

Reference 65

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:2863b2d1711da5b57d852c74fb4a3289a126bbfc4e6310286667a375f81ae2a9

Observation da530be5-fd01-4609-97da-63c72ae515d1 · outbound

This paper cites 2018 , publisher=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration 2018 , publisher=

Reference 66

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:51f7128c6a5df7026cefcc9b35652ef28f6babb4ef99fe94b80de122dda3a1b0

Observation a62d98e8-0e3e-429d-bf08-6eca046aaef2 · outbound

This paper cites 1970 , journal=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration 1970 , journal=

Reference 67

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:d35e71022238f24252af2eed6a092142515c04db463de0284a8a54f6195ce4c4

Observation 9c7b5a44-789a-42ae-b94a-18a8d3b5c86c · outbound

This paper cites Selective Learning: Towards Robust Calibration with Dynamic Regularization.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Selective Learning: Towards Robust Calibration with Dynamic Regularization

Reference 68

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verified exact
arxiv_id, observed 2026-06-30T07:54:22.230243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:dfad2bb7cda8704abbe2e8819ec9569a365ff93dded0136951c7e6be441e25b4

Observation 1a2ec06b-0e17-4dd2-88d2-c6aea009b103 · outbound

This paper cites International Conference on Learning Representations , year=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration International Conference on Learning Representations , year=

Reference 69

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:0d88ba1ddefcfd80fcc43499ea8b1aebfe9d09f6beffe93fd408f084c60f522e

Observation a37d8605-5988-40da-ad1f-bf2d46e18e86 · outbound

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

Bandwidth Selection in Kernel Density Estimation for Model Calibration Journal of Machine Learning Research , volume=

Reference 70

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:193ed16c5637bc397320cee6ed258ecc6dbf913f8031ce14c31c84275e1014df

Observation 0ccbe0b3-c120-456b-8569-14b2d98b8fcf · outbound

This paper cites A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification , booktitle =.

Bandwidth Selection in Kernel Density Estimation for Model Calibration A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification , booktitle =

Reference 71

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Observation 96dce7ec-b77e-4117-842a-44e58762fc25 · outbound

This paper cites , author=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration , author=

Reference 72

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:8da69bb12d7dd0b6abb329eac7e27f1c382a40e6fea9a0bd2672c6edf5d881d1

Observation 1da00eac-fd40-4235-bcc0-498a86e26dbd · outbound

This paper cites International Conference on Learning Representations , year=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration International Conference on Learning Representations , year=

Reference 73

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:21a8075d4965cde16c9ebb5964d0907c29478d10cedb10c875e240166d90b6bc

Observation a7416e3a-74df-49cb-aa31-5591d925f1cb · outbound

This paper cites International conference on machine learning , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration International conference on machine learning , pages=

Reference 74

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:19162639ffbf9ca9e01e227b7868729a379c30f5d7ad0b4d73922308f7b4a4d4

Observation 4a628e8d-86ca-46e9-adc4-5e44c3f624b4 · outbound

This paper cites Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=

Reference 75

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:6c166e8ad645fe37668facdbc98fcfff4fb6816c2922e6f4fd54b7c3695d567f

Observation b2e4e0e5-643e-4979-aed1-10e94ab5f081 · outbound

This paper cites International Conference on Machine Learning , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration International Conference on Machine Learning , pages=

Reference 76

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:1642d620c8da6648975f86c463e6353836f68d906ad0b9895d0e0800aeded29d

Observation 1f2acdb3-d551-4818-8d2e-0ccdf06c422e · outbound

This paper cites International Conference on Machine Learning (ICML) , pages =.

Bandwidth Selection in Kernel Density Estimation for Model Calibration International Conference on Machine Learning (ICML) , pages =

Reference 77

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:7a1d383898e4f97332609a7597c38fde5848dd37ad4aee632bc8b4728c8019dd

Observation 843fce09-a6f4-43bb-aa76-65858a7dab18 · outbound

This paper cites Advances in neural information processing systems , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Advances in neural information processing systems , volume=

Reference 78

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Observation d9e6c384-5790-4af3-8cf1-d6e78140a818 · outbound

This paper cites International conference on machine learning , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration International conference on machine learning , pages=

Reference 79

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:1287e4e0e6d33e9514918daa22c7d35220a3c1ac172fba0dd91ffa6bbdfc9199

Observation 883d082a-f711-4746-a204-0aab1ca15d0a · outbound

This paper cites an unresolved cited work.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Unresolved cited work

Reference 80

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:63ec1c06d70d6113f3a01294776aab7e16b7b2dfcc6fcfd699330e0c747886e4

Observation cf67576e-6409-4ebf-aab7-0895eaece69d · outbound

This paper cites IEEE Transactions on Pattern Analysis and Machine Intelligence , year=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration IEEE Transactions on Pattern Analysis and Machine Intelligence , year=

Reference 81

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:1a53fcb1cab906bcc8f30a2a03de337215bece0c01e10624aebbb943bbf28b38

Observation 028308e0-a045-4160-a760-4732150022c7 · outbound

This paper cites The Thirty-eighth Annual Conference on Neural Information Processing Systems , year=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration The Thirty-eighth Annual Conference on Neural Information Processing Systems , year=

Reference 82

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:1b771cf0ebede33489672819141d502c4b0152aa1eb3cd8a2ca8ecc7e3373b0b

Observation 508f4156-7873-4fd2-90fb-a1fdd500af58 · outbound

This paper cites international conference on machine learning , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration international conference on machine learning , pages=

Reference 83

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:2b700f3fc0c1608c187dd324cb7071d428c2ff6dd653e3c58318dc02b84a6a9d

Observation 186defd8-fc54-4161-bd23-e98ceaed62a1 · outbound

This paper cites Sociological Methods & Research , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Sociological Methods & Research , volume=

Reference 84

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:80ef97e78239df53f8e1a38f5d733c65af73c91ada2c901364a1418c90465e64

Observation 433efbec-8e95-4e5a-b3c3-c94f65bee6ed · outbound

This paper cites Advances in neural information processing systems , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Advances in neural information processing systems , volume=

Reference 85

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:f3127148f80b53ffc3bfb5d377d7d40de2bfbf55ddf15db3a978c468adfa83d2

Observation 65a027f9-4efe-4956-856f-58d18a23091d · outbound

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

Bandwidth Selection in Kernel Density Estimation for Model Calibration Journal of Machine Learning Research , volume=

Reference 86

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:acdbf1d5e44efb8eba42af4669aea3fbc8af98a97ffe2134f2c2e69a699c21cc

Observation a68e8712-72aa-4598-9f6a-fe58599c200a · outbound

This paper cites IEEE Transactions on computers , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration IEEE Transactions on computers , volume=

Reference 87

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:d3d64a9b28bc6db20f054b0461f58e7241c0a63b0bc4cc870ddef51a6b51d94c

Observation a4fec6b1-824f-423d-8b11-b7919960dde8 · outbound

This paper cites , author=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration , author=

Reference 88

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:f56c4e89de64b23cebaf1d2766a60db1bc685fbb22ab9da4d490e529493fa661

Observation e620178d-6a43-4bca-aa41-b08b824f1b90 · outbound

This paper cites The Twelfth International Conference on Learning Representations , year=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration The Twelfth International Conference on Learning Representations , year=

Reference 89

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:f368aa9a847b55f290d9544942645392d64fa40d3c73353e7873a90076489869

Observation 543729aa-d08e-458e-91b6-a1122ce65825 · outbound

This paper cites Conference on Learning Theory , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Conference on Learning Theory , pages=

Reference 90

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:d563599d3dbaa5dd91a79f7d02085e88d049e1c9c46ecdc1425b729dd5f175a3

Observation 1de0b287-56ef-4967-a05b-43b6c5e53879 · outbound

This paper cites International Conference on Artificial Intelligence and Statistics , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration International Conference on Artificial Intelligence and Statistics , pages=

Reference 91

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:af2a231aeae5cefe6de444e2a1fddbc987967634d4f959007fccb8a09dfedddf

Observation 936224a5-0143-4cde-96cb-54098f8f7580 · outbound

This paper cites Fifteenth International Conference on Machine Vision (ICMV 2022) , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Fifteenth International Conference on Machine Vision (ICMV 2022) , volume=

Reference 92

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:8b7eeb7c8a17fde4d3a502473469c3b9d861fb19f338ae5c456ab875d87e127e

Observation 8ca1a546-7b57-4a7c-856b-b32af3a26341 · outbound

This paper cites Proceedings of the IEEE international conference on computer vision , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Proceedings of the IEEE international conference on computer vision , pages=

Reference 93

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:4fb4e8fcd40024547d37ff287ef7717c1f0b6bdc2cc0952b773188b6e6c9d654

Observation 8e32551d-cf39-4ba0-ae1e-3f97d5d472e6 · outbound

This paper cites Monthly weather review , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Monthly weather review , volume=

Reference 94

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:acb4539585fe65c23da70940548d92f1d7b063af92831a48f8b589648c0ffa15

Observation 321b8509-aefb-4e65-9863-e9e726dcb459 · outbound

This paper cites Advances in neural information processing systems , volume=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Advances in neural information processing systems , volume=

Reference 95

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:c96680b426c2f499658beef074d5b354cd8f28090e1a35c8d9c84ccda2fc0658

Observation 5a868610-9096-4a86-bab4-3cf538d120a2 · outbound

This paper cites The Eleventh International Conference on Learning Representations , year=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration The Eleventh International Conference on Learning Representations , year=

Reference 96

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:9d2d08351a042f1d7edbf5f5796f51088ffb71410ad7b9871ad70168f55a933d

Observation 778c91c8-7d9e-4abd-a32d-03b1e946326a · outbound

This paper cites International Conference on artificial intelligence and statistics , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration International Conference on artificial intelligence and statistics , pages=

Reference 97

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:8e76556bcd9d0aeb438b9ce7b6a18d0532deda202180f0394f7dc52f490e0479

Observation 8e99858d-19f0-4587-82b4-a082661784f6 · outbound

This paper cites Optimizing Calibration by Gaining Aware of Prediction Correctness.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Optimizing Calibration by Gaining Aware of Prediction Correctness

Reference 98

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arxiv_id, observed 2026-06-30T07:54:22.233020Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:518443c7918b0d77699e91df15d070a4b3c1f3288a8b65dc5f61f2952fc0e101

Observation c15de637-461d-4c02-aaf1-04294f7416ed · outbound

This paper cites International Conference on Machine Learning , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration International Conference on Machine Learning , pages=

Reference 99

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:c6cc8f760b87e041e2796bca4636fb726872252d556bfb7a88e6a6ddbba26ef5

Observation 98706b97-7d66-44bb-a5d0-66d7cb5ef030 · outbound

This paper cites Proceedings of the 30th ACM International Conference on Multimedia , pages=.

Bandwidth Selection in Kernel Density Estimation for Model Calibration Proceedings of the 30th ACM International Conference on Multimedia , pages=

Reference 100

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source=arxiv_source observed=2026-06-30T07:48:52.228289Z digest=sha256:e5b1720b140b348afc5ef87e424e467e70f17ca5466bb0efe853b04624d97971

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