Bertlmann-Martin inequalities in hypernucleidoi:10.1103/PhysRevC.50.2900R J LombardSaturnino MarcosJ Mares
Martin Hořeňovský found a way for a 2x speedup for the compilation time of the test suite. ukhegg found proposed an improvement for the examples section. rswanson-ihi noted a typo in the README. Mihai Stan fixed a bug in the comparison with nullptrs. Tushar Maheshwari added cotire ...
Jingyu Liu, Tal Remez, Jérémy Rapin, Artyom Kozhevnikov, Ivan Evtimov, Joanna Bitton, Manish Bhatt, Cristian Canton Ferrer, Aaron Grattafiori, Wenhan Xiong, Alexandre Défossez, Jade Copet, Faisal Azhar, Hugo Touvron, Louis Martin, Nicolas Usunier, Thomas Scialom, Gabriel Synnaeve 发布...
Overall, this work provides a valuable contribution to the development of COVID-19 related NLP models.Martin MüllerMarcel SalathéPer E. KummervoldFrontiers In Artificial Intelligence
Finally, we interpretedMetBERT at different scales and revealed a possible association betweenradiation therapy and metastasis risk in multiple cancer types.Ke LiuOmkar KulkarniMartin Witteveen-LaneBin ChenDave CheslaAMIA Summits on Translational Science Proceedings...
Highlighting the potential for cross-fertilizing AI with libraries, the conclusion suggests that while AI may transform the workings of the library, libraries can also play a key role in the future development of AI.doi:10.5860/crl.84.1.30Chris Haffenden...
Large-scale use of this text-encoded information requires converting the unstructuredtext to a structured, semantic representation. We explore the extraction and normalization ofanatomical information in radiology reports that is associated with radiological findings. Weinvestigate this extraction and ...
First, we utilized the BERT model to obtain the maximum hidden state for each token, as detailed in BERT-DOC-TOK-SEG [19], so as to obtain the sequence of processed tokens t=(t1,t2,...,tnt)t=(t1,t2,...,tnt). Then, we used external knowledge to annotate the keywords in the ar...
First, we utilized the BERT model to obtain the maximum hidden state for each token, as detailed in BERT-DOC-TOK-SEG [19], so as to obtain the sequence of processed tokens t=(t1,t2,...,tnt)t=(t1,t2,...,tnt). Then, we used external knowledge to annotate the keywords in the ar...