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| Comments: | Accepted to the Applied Data Science (ADS) track at the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2026) |
| Subjects: | Information Retrieval (cs.IR); Machine Learning (cs.LG) |
| ACM classes: | I.2.7; H.3.3; I.2.4 |
| Cite as: | arXiv:2604.26197 [cs.IR] |
| (or arXiv:2604.26197v2 [cs.IR] for this version) | |
| https://doi.org/10.48550/arXiv.2604.26197 arXiv-issued DOI via DataCite |
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| Related DOI: | https://doi.org/10.1145/3770855.3818432
DOI(s) linking to related resources |
From: Zhentao Xu [view email]
[v1]
Wed, 29 Apr 2026 00:53:52 UTC (805 KB)
[v2]
Mon, 25 May 2026 18:14:23 UTC (954 KB)
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