Zobrazeno 1 - 10
of 30 323
pro vyhledávání: '"A. Bergen"'
Autor:
K. Krause, F. Wittrock, A. Richter, D. Busch, A. Bergen, J. P. Burrows, S. Freitag, O. Halbherr
Publikováno v:
Atmospheric Measurement Techniques, Vol 16, Pp 1767-1787 (2023)
Inland ships are an important source of NOx, especially for cities along busy waterways. The amount and effect of such emissions depend on the traffic density and NOx emission rates of individual vessels. Ship emission rates are typically derived usi
Externí odkaz:
https://doaj.org/article/a1ec06c97180491aa777234f13cf0649
Autor:
Arnett, Catherine, Bergen, Benjamin K.
Language models perform differently across languages. It has been previously suggested that morphological typology may explain some of this variability (Cotterell et al., 2018). We replicate previous analyses and find additional new evidence for a pe
Externí odkaz:
http://arxiv.org/abs/2411.14198
Diestel, Hundertmark and Lemanczyk asked whether every $k$-tangle in a graph is induced by a set of vertices by majority vote. We reduce their question to graphs whose size is bounded by a function in $k$. Additionally, we show that if for any fixed
Externí odkaz:
http://arxiv.org/abs/2411.13656
Autor:
Lyu, Bohan, Cao, Yadi, Watson-Parris, Duncan, Bergen, Leon, Berg-Kirkpatrick, Taylor, Yu, Rose
Large Language Models (LLMs) demonstrate promising capabilities in solving simple scientific problems but often produce hallucinations for complex ones. While integrating LLMs with tools can increase reliability, this approach typically results in ov
Externí odkaz:
http://arxiv.org/abs/2411.00412
Prototype-based methods are intrinsically interpretable XAI methods that produce predictions and explanations by comparing input data with a set of learned prototypical examples that are representative of the training data. In this work, we discuss a
Externí odkaz:
http://arxiv.org/abs/2410.19856
Autor:
Manivannan, Veeramakali Vignesh, Jafari, Yasaman, Eranky, Srikar, Ho, Spencer, Yu, Rose, Watson-Parris, Duncan, Ma, Yian, Bergen, Leon, Berg-Kirkpatrick, Taylor
The use of foundation models in climate science has recently gained significant attention. However, a critical issue remains: the lack of a comprehensive evaluation framework capable of assessing the quality and scientific validity of model outputs.
Externí odkaz:
http://arxiv.org/abs/2410.16701
For many low-resource languages, the only available language models are large multilingual models trained on many languages simultaneously. However, using FLORES perplexity as a metric, we find that these models perform worse than bigrams for many la
Externí odkaz:
http://arxiv.org/abs/2408.10441
Autor:
Thach, Nguyen, Habecker, Patrick, Johnston, Bergen, Cervantes, Lillianna, Eisenbraun, Anika, Mason, Alex, Tyler, Kimberly, Khan, Bilal, Chan, Hau
Substance use is a global issue that negatively impacts millions of persons who use drugs (PWUDs). In practice, identifying vulnerable PWUDs for efficient allocation of appropriate resources is challenging due to their complex use patterns (e.g., the
Externí odkaz:
http://arxiv.org/abs/2407.13047
Everyday AI detection requires differentiating between people and AI in informal, online conversations. In many cases, people will not interact directly with AI systems but instead read conversations between AI systems and other people. We measured h
Externí odkaz:
http://arxiv.org/abs/2407.08853
We propose a prototype-based approach for improving explainability of softmax classifiers that provides an understandable prediction confidence, generated through stochastic sampling of prototypes, and demonstrates potential for out of distribution d
Externí odkaz:
http://arxiv.org/abs/2407.02271