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Several recent works seek to develop foundation models specifically for medical applications, adapting general-purpose large language models (LLMs) and vision-language models (VLMs) via continued pretraining on publicly available biomedical corpora.
Externí odkaz:
http://arxiv.org/abs/2411.08870
Several recent works seek to develop foundation models specifically for medical applications, adapting general-purpose large language models (LLMs) and vision-language models (VLMs) via continued pretraining on publicly available biomedical corpora.
Externí odkaz:
http://arxiv.org/abs/2411.04118
While many works have studied statistical data fusion, they typically assume that the various datasets are given in advance. However, in practice, estimation requires difficult data collection decisions like determining the available data sources, th
Externí odkaz:
http://arxiv.org/abs/2411.03195
In this work, we investigate the causal reasoning abilities of large language models (LLMs) through the representative problem of inferring causal relationships from narratives. We find that even state-of-the-art language models rely on unreliable sh
Externí odkaz:
http://arxiv.org/abs/2410.23884
Fairness metrics are a core tool in the fair machine learning literature (FairML), used to determine that ML models are, in some sense, "fair". Real-world data, however, are typically plagued by various measurement biases and other violated assumptio
Externí odkaz:
http://arxiv.org/abs/2410.09600
Autor:
Addison, Joanne
Publikováno v:
College Composition and Communication, 2016 Dec 01. 68(2), 372-374.
Externí odkaz:
https://www.jstor.org/stable/44783566
As recommender systems become widely deployed in different domains, they increasingly influence their users' beliefs and preferences. Auditing recommender systems is crucial as it not only ensures the continuous improvement of recommendation algorith
Externí odkaz:
http://arxiv.org/abs/2409.13210
Autor:
Hou, Wenyuan, Stubbs, Timothy, DeBeer-Schmitt, Lisa, Chang, Yen-Ting, Charpagne, Marie-Agathe, Smith, Timothy M., Huang, Aijun, Cordero, Zachary C.
The structural evolution of oxides in dispersion-strengthened superalloys during laser-powder bed fusion is considered in detail. Alloy chemistry and process parameter effects on oxide structure are assessed through a parameter study on the model all
Externí odkaz:
http://arxiv.org/abs/2408.01845
Autor:
Scholz, Stefan, Weidmann, Nils B., Steinert-Threlkeld, Zachary C., Keremoğlu, Eda, Goldlücke, Bastian
Treating images as data has become increasingly popular in political science. While existing classifiers for images reach high levels of accuracy, it is difficult to systematically assess the visual features on which they base their classification. T
Externí odkaz:
http://arxiv.org/abs/2407.03786