Zobrazeno 1 - 10
of 284
pro vyhledávání: '"Michelle, Chen"'
Autor:
Bulian, Jannis, Schäfer, Mike S., Amini, Afra, Lam, Heidi, Ciaramita, Massimiliano, Gaiarin, Ben, Hübscher, Michelle Chen, Buck, Christian, Mede, Niels G., Leippold, Markus, Strauß, Nadine
Publikováno v:
Proceedings of the 41st International Conference on Machine Learning (ICML), 2024
As Large Language Models (LLMs) rise in popularity, it is necessary to assess their capability in critically relevant domains. We present a comprehensive evaluation framework, grounded in science communication research, to assess LLM responses to que
Externí odkaz:
http://arxiv.org/abs/2310.02932
Autor:
Demy Dam, Michelle Chen, Erin E. Rees, Bethany Cheng, Lynn Sukkarieh, Erin McGill, Yasmina Tehami, Anna Bellos, Jonathan Edwin, Kaitlin Patterson
Publikováno v:
BMC Public Health, Vol 24, Iss 1, Pp 1-11 (2024)
Abstract Background The severity of COVID-19 outbreaks is disproportionate across settings (e.g., long-term care facilities (LTCF), schools) across Canada. Few studies have examined factors associated with outbreak severity to inform prevention and r
Externí odkaz:
https://doaj.org/article/8d8babb8dc7f4107a6b06e3426ca2de7
Publikováno v:
ACS Omega, Vol 9, Iss 35, Pp 37076-37085 (2024)
Externí odkaz:
https://doaj.org/article/ef873373f8e5475baa5dafd0ae96a81d
Autor:
Adolphs, Leonard, Huebscher, Michelle Chen, Buck, Christian, Girgin, Sertan, Bachem, Olivier, Ciaramita, Massimiliano, Hofmann, Thomas
Neural retrieval models have superseded classic bag-of-words methods such as BM25 as the retrieval framework of choice. However, neural systems lack the interpretability of bag-of-words models; it is not trivial to connect a query change to a change
Externí odkaz:
http://arxiv.org/abs/2210.12084
Learning to search is the task of building artificial agents that learn to autonomously use a search box to find information. So far, it has been shown that current language models can learn symbolic query reformulation policies, in combination with
Externí odkaz:
http://arxiv.org/abs/2209.15469
Publikováno v:
Cancers, Vol 16, Iss 16, p 2817 (2024)
LOX was recently shown to inhibit cancer cell proliferation and tumor growth. The mechanism of this inhibition, however, has been exclusively attributed to LOX depletion of TME lactate, a cancer cell energy source, and production of H2O2, an oxidativ
Externí odkaz:
https://doaj.org/article/91c8b9337c314a8984ccc4f91f49a682
Autor:
Adolphs, Leonard, Boerschinger, Benjamin, Buck, Christian, Huebscher, Michelle Chen, Ciaramita, Massimiliano, Espeholt, Lasse, Hofmann, Thomas, Kilcher, Yannic, Rothe, Sascha, Sessa, Pier Giuseppe, Saralegui, Lierni Sestorain
This paper presents first successful steps in designing search agents that learn meta-strategies for iterative query refinement in information-seeking tasks. Our approach uses machine reading to guide the selection of refinement terms from aggregated
Externí odkaz:
http://arxiv.org/abs/2109.00527
Autor:
George Zhou, Yunchan Chen, Candace Chien, Leslie Revatta, Jannatul Ferdous, Michelle Chen, Shourov Deb, Sol De Leon Cruz, Alan Wang, Benjamin Lee, Mert R. Sabuncu, William Browne, Herrick Wun, Bobak Mosadegh
Publikováno v:
npj Digital Medicine, Vol 6, Iss 1, Pp 1-14 (2023)
Abstract For hemodialysis patients, arteriovenous fistula (AVF) patency determines whether adequate hemofiltration can be achieved, and directly influences clinical outcomes. Here, we report the development and performance of a deep learning model fo
Externí odkaz:
https://doaj.org/article/6e8fdb3e06ce4b32b03620b5aa7b25a3
Autor:
Borschinger, Benjamin, Boyd-Graber, Jordan, Buck, Christian, Bulian, Jannis, Ciaramita, Massimiliano, Huebscher, Michelle Chen, Gajewski, Wojciech, Kilcher, Yannic, Nogueira, Rodrigo, Saralegu, Lierni Sestorain
We investigate a framework for machine reading, inspired by real world information-seeking problems, where a meta question answering system interacts with a black box environment. The environment encapsulates a competitive machine reader based on BER
Externí odkaz:
http://arxiv.org/abs/1911.04156
Autor:
Yousef Javanmardi, Ayushi Agrawal, Andrea Malandrino, Soufian Lasli, Michelle Chen, Somayeh Shahreza, Bianca Serwinski, Leila Cammoun, Ran Li, Mehdi Jorfi, Boris Djordjevic, Nicolas Szita, Fabian Spill, Sergio Bertazzo, Graham K Sheridan, Vivek Shenoy, Fernando Calvo, Roger Kamm, Emad Moeendarbary
Publikováno v:
Advanced Science, Vol 10, Iss 16, Pp n/a-n/a (2023)
Abstract Cancer cell extravasation, a key step in the metastatic cascade, involves cancer cell arrest on the endothelium, transendothelial migration (TEM), followed by the invasion into the subendothelial extracellular matrix (ECM) of distant tissues
Externí odkaz:
https://doaj.org/article/28f88a3bdf124cc89be1eea1ffbeb641