OpenML
PulseAugur coverage of OpenML — every cluster mentioning OpenML across labs, papers, and developer communities, ranked by signal.
1 天有情绪数据
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New studies probe tabular foundation model mechanisms and ensembling
Two new research papers delve into the intricacies of tabular foundation models (TFMs), exploring their performance and ensemble strategies. The first paper provides a mechanistic study, analyzing how different TFM arch…
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New method tackles label shift in tabular foundation models
Researchers have introduced DistPFN, a novel method to address label shift in tabular foundation models like TabPFN. This technique adjusts predictions at test time by re-weighting the influence of training data's class…
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PUICL transformer enables in-context positive-unlabeled learning without fitting
Researchers have developed PUICL, a pretrained transformer model capable of performing positive-unlabeled (PU) learning through in-context learning. This approach eliminates the need for dataset-specific training or ite…
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ScoringBench: A Benchmark for Evaluating Tabular Foundation Models with Proper Scoring Rules
Two new research papers introduce methods for better evaluating and cleaning tabular foundation models. ScoringBench offers a comprehensive benchmark using proper scoring rules to assess model performance beyond simple …