Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T14:52:45.604805Z
Paper Citation Record · LEDGER
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement
As of 19 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2508.20824.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
49 of 49 outbound references displayed
- verified exact4
- verified fuzzy26
- unresolved18
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 4dfbf1ad-a813-499e-b57e-1023252a916e · outbound
This paper cites Journal of machine Learning research 3(Jan), 993–1022 (2003).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Journal of machine Learning research 3(Jan), 993–1022 (2003)
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.284600Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 8a6f2ac8-a4f3-4c58-8b02-378be4fdd78b · outbound
This paper cites UCI Machine Learning Repository (2010), DOI: https://doi.org/10.24432/C5H30K.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement UCI Machine Learning Repository (2010), DOI: https://doi.org/10.24432/C5H30K
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:52:45.403859Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 84ae18f4-83d7-417f-b514-a54a1b4c5e0b · outbound
This paper cites In: 2019 IEEE International Conference on Data Mining (ICDM).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement In: 2019 IEEE International Conference on Data Mining (ICDM)
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.269384Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 3369a334-856f-4629-a4d7-3d1a7bd1abd9 · outbound
This paper cites ACM SIGKDD Explorations Newsletter22(2), 35–50 (2021).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement ACM SIGKDD Explorations Newsletter22(2), 35–50 (2021)
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.255677Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 3ef4b686-4412-4232-8d69-c62a10074bd3 · outbound
This paper cites UCI Machine Learning Repository (2009), DOI: https://doi.org/10.24432/C56S3T.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement UCI Machine Learning Repository (2009), DOI: https://doi.org/10.24432/C56S3T
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:52:45.417451Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 41a64a54-0d1f-41c7-81d3-df71ade5ca8c · outbound
This paper cites UCI Machine Learning Reposi- tory (2009), DOI: https://doi.org/10.24432/C5GC82.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement UCI Machine Learning Reposi- tory (2009), DOI: https://doi.org/10.24432/C5GC82
Reference 6
- Resolution
- verified exact
- doi, observed 2026-08-05T14:52:45.691982Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 827046d3-b757-46ca-803d-4668020c4d50 · outbound
This paper cites Infor- mation Sciences 189, 176–190 (2012).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Infor- mation Sciences 189, 176–190 (2012)
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.241648Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation cf49f14e-e718-41b2-b9e1-7daaf45392c7 · outbound
This paper cites The Journal of Machine Learning Research20(1), 1997–2017 (2019).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement The Journal of Machine Learning Research20(1), 1997–2017 (2019)
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.227597Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 93e466b2-aace-400c-923c-ae7388e4f720 · outbound
This paper cites The Journal of Supercomputing 80(18), 26394–26434 (2024).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement The Journal of Supercomputing 80(18), 26394–26434 (2024)
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.213170Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 0eee8665-9570-4729-b9e9-96fb6039b8b3 · outbound
This paper cites Knowledge- Based Systems 212, 106622 (2021).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Knowledge- Based Systems 212, 106622 (2021)
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.198402Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 8dd2525b-3fdf-4889-8c4f-d3b9450d2ded · outbound
This paper cites The autofeat Python Library for Automated Feature Engineering and Selection.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement The autofeat Python Library for Automated Feature Engineering and Selection
Reference 11
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-05T14:52:45.775569Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 8f74bcec-d0fd-4892-bae2-92753efc057a · outbound
This paper cites In: Machine Learning and Knowledge Discovery in Databases: International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part I.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement In: Machine Learning and Knowledge Discovery in Databases: International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part I
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.183400Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation b5d5752f-ca1d-4b0b-b4b8-2fac2598e666 · outbound
This paper cites an unresolved cited work.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Unresolved cited work
Reference 13
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T14:52:46.168094Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 05506e13-403d-47a7-b9b8-6df5d13f7e32 · outbound
This paper cites an unresolved cited work.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Unresolved cited work
Reference 14
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T14:52:46.153198Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d539004e-ece0-40dc-91cb-e28651f4655d · outbound
This paper cites UCI Machine Learning Repository (1989), DOI: https://doi.org/10.24432/C52P4X.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement UCI Machine Learning Repository (1989), DOI: https://doi.org/10.24432/C52P4X
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:52:45.461102Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8ac7e656-2e33-427c-ad73-18144c966e99 · outbound
This paper cites Jour- nal of Statistics Education4 (1996), http://www.amstat.org/publications/jse/ v4n1/datasets.johnson.html, bodyfat data retrieved from the American Statis- tical Association.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Jour- nal of Statistics Education4 (1996), http://www.amstat.org/publications/jse/ v4n1/datasets.johnson.html, bodyfat data retrieved from the American Statis- tical Association
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.139086Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 1c7a1862-e1ec-4c59-ba88-9163d67793d1 · outbound
This paper cites an unresolved cited work.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Unresolved cited work
Reference 17
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T14:52:46.125353Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 37524117-0c8a-4503-ba17-8723beb6bb2f · outbound
This paper cites In: 2015 IEEE international conference on data science and advanced analytics (DSAA).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement In: 2015 IEEE international conference on data science and advanced analytics (DSAA)
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.112724Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 0e78114b-365c-46e1-a6dd-6c5d5eb13663 · outbound
This paper cites ACM Computing Surveys (CSUR) 54(8), 1–36 (2021).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement ACM Computing Surveys (CSUR) 54(8), 1–36 (2021)
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.099860Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 50a856e4-3535-4cf1-a5f5-0ad1ff917e29 · outbound
This paper cites In: 2016 IEEE 16th International Conference on Data Mining (ICDM).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement In: 2016 IEEE 16th International Conference on Data Mining (ICDM)
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.086875Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation be9a7957-4aa5-487d-9740-6c3e6726bde2 · outbound
This paper cites an unresolved cited work.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Unresolved cited work
Reference 21
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T14:52:46.072363Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation a0cf83e3-2d2b-493e-9003-1896d8e5d2e7 · outbound
This paper cites Transformation10(10), 10 (2016).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Transformation10(10), 10 (2016)
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.058972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 94e24b2d-d055-4e3f-b84e-1e75fe37afdd · outbound
This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement In: Proceedings of the AAAI Conference on Artificial Intelligence
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.044986Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation f0f3030f-2ee6-470a-809b-91be13e59158 · outbound
This paper cites In: 2016 IEEE 16th international con- ference on data mining workshops (ICDMW).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement In: 2016 IEEE 16th international con- ference on data mining workshops (ICDMW)
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.031525Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation c3f54baa-9309-4822-a3de-9aa69bf5098e · outbound
This paper cites IEEE Transactions on Electronics Packaging Manufacturing24(3), 214–221 (2001).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement IEEE Transactions on Electronics Packaging Manufacturing24(3), 214–221 (2001)
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.018428Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ae4115b2-d50f-45ea-a5db-fcabc895a81b · outbound
This paper cites One button machine for automating feature engineering in relational databases.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement One button machine for automating feature engineering in relational databases
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:52:45.506689Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e456b52f-682c-4694-97e8-0fb4d43802c3 · outbound
This paper cites In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:46.005123Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 0c05a138-b51f-4eda-b97a-4111a3ffb22c · outbound
This paper cites UCI Machine Learning Repository (1999), DOI: https://doi.org/10.24432/C59W2D.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement UCI Machine Learning Repository (1999), DOI: https://doi.org/10.24432/C59W2D
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:52:45.515293Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5a25f437-8072-4f06-bd1d-77ff5d9b4a3f · outbound
This paper cites In: Pro- ceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement In: Pro- ceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:45.991745Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e5b889ea-10b9-4a74-a447-868e3003a65b · outbound
This paper cites In: 2024 IEEE International Conference on Big Data (BigData).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement In: 2024 IEEE International Conference on Big Data (BigData)
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:45.978608Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e2063b15-51fd-489a-a2a0-b5d685201b8d · outbound
This paper cites an unresolved cited work.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Unresolved cited work
Reference 31
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T14:52:45.965316Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation b78fe2f2-89d5-4b91-be2f-50f2f9548aa4 · outbound
This paper cites an unresolved cited work.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Unresolved cited work
Reference 32
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T14:52:45.951952Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 1a017169-70b9-46bb-95d6-0d148ca77eaf · outbound
This paper cites In: Proceedings of the genetic and evolutionary computation conference 2016.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement In: Proceedings of the genetic and evolutionary computation conference 2016
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:45.938241Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ebbe30f9-469d-423c-9dfe-0d657f1d843b · outbound
This paper cites an unresolved cited work.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Unresolved cited work
Reference 34
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T14:52:45.923636Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 8958c7fb-f578-4723-af15-a4a3c0845fef · outbound
This paper cites an unresolved cited work.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Unresolved cited work
Reference 35
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T14:52:45.910771Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation a0eb3e74-79d2-492d-b113-b80abe47f0bb · outbound
This paper cites an unresolved cited work.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Unresolved cited work
Reference 36
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T14:52:45.897692Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 41deb697-0d54-495f-b0e2-7d0b2f2a2b60 · outbound
This paper cites an unresolved cited work.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Unresolved cited work
Reference 37
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T14:52:45.884409Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation fd5d68b0-9baf-42b9-8937-2367e5fdda6a · outbound
This paper cites Memetic Computing8(1), 3–15 (2016).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Memetic Computing8(1), 3–15 (2016)
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:45.870797Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 775b81ad-e248-45cc-9245-9e45540b2fa6 · outbound
This paper cites Pattern Recognition93, 404–417 (2019).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Pattern Recognition93, 404–417 (2019)
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:45.857360Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation af95bbc2-fb3f-4fae-849d-14a98aade557 · outbound
This paper cites In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:45.842960Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 345f2166-bc50-4df0-94b1-65eb5aba23e5 · outbound
This paper cites Advances in Neural Information Processing Systems36, 43563–43578 (2023).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Advances in Neural Information Processing Systems36, 43563–43578 (2023)
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:45.829067Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 059b9ce7-a4ed-47f1-8815-fa4530d3270e · outbound
This paper cites Iterative Feature Space Optimization through Incremental Adaptive Evaluation.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Iterative Feature Space Optimization through Incremental Adaptive Evaluation
Reference 42
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T14:52:45.741316Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 219e9771-a262-4c4a-bce1-c9e0509c093f · outbound
This paper cites Traceable Group-Wise Self-Optimizing Feature Transformation Learning: A Dual Optimization Perspective.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Traceable Group-Wise Self-Optimizing Feature Transformation Learning: A Dual Optimization Perspective
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:52:45.580647Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 92934930-e075-42c4-afcb-1844b837d2b4 · outbound
This paper cites In: Pro- ceedings of the 2023 SIAM International Conference on Data Mining (SDM).
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement In: Pro- ceedings of the 2023 SIAM International Conference on Data Mining (SDM)
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:45.815881Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 696ddf95-8fc2-4a72-b5ea-baf8c90ea411 · outbound
This paper cites UCI Machine Learning Repository (2008), DOI: https://doi.org/10.24432/C5NG6W.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement UCI Machine Learning Repository (2008), DOI: https://doi.org/10.24432/C5NG6W
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T14:52:45.588705Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d4f970fe-c008-46c6-9a2b-99f762203bb7 · outbound
This paper cites UCI Machine Learning Repository (2014), DOI: https://doi.org/10.24432/C5VK5D.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement UCI Machine Learning Repository (2014), DOI: https://doi.org/10.24432/C5VK5D
Reference 46
- Resolution
- verified exact
- doi, observed 2026-08-05T14:52:45.653182Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation f5d56de4-8637-4249-b9f4-7a7c087034af · outbound
This paper cites an unresolved cited work.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Unresolved cited work
Reference 47
- Resolution
- unresolved
- raw_fallback, observed 2026-08-05T14:52:45.802621Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 1da893b6-11a9-4273-a60a-19db98affb8e · outbound
This paper cites In: International Conference on Automated Machine Learning.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement In: International Conference on Automated Machine Learning
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-05T14:52:45.789987Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 98998c22-feee-499c-b3d2-7dc74658efe5 · outbound
This paper cites an unresolved cited work.
GPT-FT: An Efficient Automated Feature Transformation Using GPT for Sequence Reconstruction and Performance Enhancement Unresolved cited work
Reference 49
- Resolution
- verified exact
- doi, observed 2026-08-05T14:52:45.640016Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Pith citing papers
No inbound Pith citation observations are available.