Customer-obsessed science
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November 20, 20254 min readA new evaluation pipeline called FiSCo uncovers hidden biases and offers an assessment framework that evolves alongside language models.
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October 2, 20253 min read
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September 2, 20253 min read
Featured news
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Machine Learning and Knowledge Extraction2023We propose and implement an interpretable machine learning classification model for Explainable AI (XAI) based on expressive Boolean formulas. Potential applications include credit scoring and diagnosis of medical conditions. The Boolean formula defines a rule with tunable complexity (or interpretability), according to which input data are classified. Such a formula can include any operator that can be
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NeurIPS 20232023Code completion models have made significant progress in recent years, yet current popular evaluation datasets, such as HumanEval and MBPP, predominantly focus on code completion tasks within a single file. This oversimplified setting falls short of representing the real-world software development scenario where repositories span multiple files with numerous cross-file dependencies, and accessing and understanding
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EMNLP 20232023Generating concise summaries of news events is a challenging natural language processing task. While journalists often curate timelines to highlight key sub-events, newcomers to a news event face challenges in catching up on its historical context. In this paper, we address this need by introducing the task of background news summarization, which complements each timeline update with a background summary
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Social Science Research Network2023We present a procurement model for highly seasonal products, such as toys or fashion products, which are usually purchased through a combination of import and domestic buys, months ahead of typical vendor lead times, with potential riskier buys just-in-time. This procurement process differs significantly from the more common just-in-time buying, or repeated dual sourcing, since the decision to split orders
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NeurIPS 20232023Modeling customer shopping intentions is a crucial task for e-commerce, as it directly impacts user experience and engagement. Thus, accurately understanding customer preferences is essential for providing personalized recommendations. Session-based recommendation, which utilizes customer session data to predict their next interaction, has become increasingly popular. However, existing session datasets
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