Decomposing the Brain in Autism: Linking Behavioral Domains to Neuroanatomical Variation and Genomic Underpinnings.
Hanna Seelemeyer
Caroline Gurr
Johanna Leyhausen
Lisa M. Berg
Charlotte M. Pretzsch
Tim Schäfer
Bassem Hermila
Christine M. Freitag
Eva Loth
Beth Oakley
Luke Mason
Jan K. Buitelaar
Christian Beckmann
Dorothea L. Floris
Tony Charman
Tobias Banaschewski
Thomas Bourgeron
Jumana Ahmad
Sara Ambrosino
Bonnie Auyeung … (voir 56 de plus)
Simon Baron-Cohen
Sarah Baumeister
Sven Bölte
Carsten Bours
Michael Brammer
Daniel Brandeis
Claudia Brogna
Yvette de Bruijn
Bhismadev Chakrabarti
Ineke Cornelissen
Daisy Crawley
Flavio Dell’Acqua
Sarah Durston
Christine Ecker
Jessica Faulkner
Vincent Frouin
Pilar Garcés
David Goyard
Lindsay Ham
Hannah Hayward
Joerg F. Hipp
Rosemary Holt
Mark Johnson
Emily J. H. Jones
Prantik Kundu
Meng-Chuan Lai
Xavier Liogier D’ardhuy
Michael V. Lombardo
David J. Lythgoe
René Mandl
Andre Marquand
Maarten Mennes
Andreas Meyer-Lindenberg
Carolin Moessnang
Nico Bast
Laurence O’Dwyer
Marianne Oldehinkel
Bob Oranje
Gahan Pandina
Antonio Persico
Barbara Ruggeri
Amber N. V. Ruigrok
Jessica Sabet
Roberto Sacco
Antonia San José Cáceres
Emily Simonoff
Will Spooren
Julian Tillmann
Roberto Toro
Heike Tost
Jack Waldman
Steve C.R. Williams
Caroline Wooldridge
Marcel P. Zwiers
Declan Murphy
Decomposing the Brain in Autism: Linking Behavioral Domains to Neuroanatomical Variation and Genomic Underpinnings.
Hanna Seelemeyer
Caroline Gurr
Johanna Leyhausen
Lisa M. Berg
Charlotte M. Pretzsch
Tim Schäfer
Bassem Hermila
Christine M. Freitag
Eva Loth
Beth Oakley
Luke Mason
Jan K. Buitelaar
Christian Beckmann
Dorothea L. Floris
Tony Charman
Tobias Banaschewski
Thomas Bourgeron
Jumana Ahmad
Sara Ambrosino
Bonnie Auyeung … (voir 56 de plus)
Simon Baron-Cohen
Sarah Baumeister
Sven Bölte
Carsten Bours
Michael Brammer
Daniel Brandeis
Claudia Brogna
Yvette de Bruijn
Bhismadev Chakrabarti
Ineke Cornelissen
Daisy Crawley
Flavio Dell’Acqua
Sarah Durston
Christine Ecker
Jessica Faulkner
Vincent Frouin
Pilar Garcés
David Goyard
Lindsay Ham
Hannah Hayward
Joerg F. Hipp
Rosemary Holt
Mark Johnson
Emily J. H. Jones
Prantik Kundu
Meng-Chuan Lai
Xavier Liogier D’ardhuy
Michael V. Lombardo
David J. Lythgoe
René Mandl
Andre Marquand
Maarten Mennes
Andreas Meyer-Lindenberg
Carolin Moessnang
Nico Bast
Laurence O’Dwyer
Marianne Oldehinkel
Bob Oranje
Gahan Pandina
Antonio Persico
Barbara Ruggeri
Amber N. V. Ruigrok
Jessica Sabet
Roberto Sacco
Antonia San José Cáceres
Emily Simonoff
Will Spooren
Julian Tillmann
Roberto Toro
Heike Tost
Jack Waldman
Steve C. R. Williams
Caroline Wooldridge
Marcel P. Zwiers
Declan Murphy
Decomposing the Brain in Autism: Linking Behavioral Domains to Neuroanatomical Variation and Genomic Underpinnings.
Hanna Seelemeyer
Caroline Gurr
Johanna Leyhausen
Lisa M. Berg
Charlotte M. Pretzsch
Tim Schäfer
Bassem Hermila
Christine M. Freitag
Eva Loth
Beth Oakley
Luke Mason
Jan K. Buitelaar
Christian Beckmann
Dorothea L. Floris
Tony Charman
Tobias Banaschewski
Emily Jones
Thomas Bourgeron
Jumana Ahmad
Sara Ambrosino … (voir 58 de plus)
Bonnie Auyeung
Simon Baron-Cohen
Sarah Baumeister
Sven Bölte
Carsten Bours
Michael Brammer
Daniel Brandeis
Claudia Brogna
Yvette de Bruijn
Bhismadev Chakrabarti
Ineke Cornelissen
Daisy Crawley
Flavio Dell’Acqua
Sarah Durston
Christine Ecker
Jessica Faulkner
Vincent Frouin
Pilar Garcés
David Goyard
Lindsay Ham
Hannah Hayward
Joerg F. Hipp
Rosemary Holt
Mark Johnson
Emily J. H. Jones
Prantik Kundu
Meng-Chuan Lai
Xavier Liogier D’ardhuy
Michael V. Lombardo
David J. Lythgoe
René Mandl
Andre Marquand
Maarten Mennes
Andreas Meyer-Lindenberg
Carolin Moessnang
Nico Bast
Laurence O’Dwyer
Marianne Oldehinkel
Bob Oranje
Gahan Pandina
Antonio Persico
Barbara Ruggeri
Declan G.M. Murphy
Amber N. V. Ruigrok
Jessica Sabet
Roberto Sacco
Antonia San José Cáceres
Emily Simonoff
Will Spooren
Julian Tillmann
Roberto Toro
Heike Tost
Jack Waldman
Steve C. R. Williams
Caroline Wooldridge
Marcel P. Zwiers
Declan Murphy
Ensemble machine learning to accelerate industrial decarbonization: Prediction of Hansen solubility parameters for streamlined chemical solvent selection
Eslam G. Al-Sakkari
Ahmed Ragab
Mostafa Amer
Olumoye Ajao
Marzouk Benali
Daria Camilla Boffito
Mouloud Amazouz
Ensemble machine learning to accelerate industrial decarbonization: Prediction of Hansen solubility parameters for streamlined chemical solvent selection
Eslam G. Al-Sakkari
Ahmed Ragab
Mostafa Amer
Olumoye Ajao
Marzouk Benali
Daria Camilla Boffito
Mouloud Amazouz
Learning adversarially robust kernel ensembles with kernel average pooling
Reza Bayat
Adam Ibrahim
Amirozhan Dehghani
Yifei Ren
Learning adversarially robust kernel ensembles with kernel average pooling
Reza Bayat
Adam Ibrahim
Amirozhan Dehghani
Yifei Ren
Learning adversarially robust kernel ensembles with kernel average pooling
Reza Bayat
Adam Ibrahim
Amirozhan Dehghani
Yifei Ren
Patient Engagement in the Implementation of Electronic Patient-Reported Outcome Tools: The Experience of Two Early-Adopter Institutions in the Pan-Canadian Radiotherapy Patient-Reported Outcome Initiative
Amanda Caissie
J. Lane
B. Barber
S. Chisholm
Patient Engagement in the Implementation of Electronic Patient Reported Outcome (ePRO) Tools: The Experience of Two Early Adopter Institutions in the pan-Canadian Radiotherapy PRO Initiative
Amanda Caissie
Jennifer Lane
Brittany V Barber
Sue Chisholm
Predicting the Mathematics Literacy of Resilient Students from High‐performing Economies: A Machine Learning Approach
Yimei Zhang
Uhura: A Benchmark for Evaluating Scientific Question Answering and Truthfulness in Low-Resource African Languages
Edward Bayes
Israel Abebe Azime
Jesujoba Oluwadara Alabi
Jonas Kgomo
Tyna Eloundou
Elizabeth Proehl
Kai Chen
Imaan Khadir
Naome Etori
Shamsuddeen Hassan Muhammad
C. Mpanza
Igneciah Pocia Thete
Dietrich Klakow
Evaluations of Large Language Models (LLMs) on knowledge-intensive tasks and factual accuracy often focus on high-resource languages primari… (voir plus)ly because datasets for low-resource languages (LRLs) are scarce. In this paper, we present Uhura -- a new benchmark that focuses on two tasks in six typologically-diverse African languages, created via human translation of existing English benchmarks. The first dataset, Uhura-ARC-Easy, is composed of multiple-choice science questions. The second, Uhura-TruthfulQA, is a safety benchmark testing the truthfulness of models on topics including health, law, finance, and politics. We highlight the challenges creating benchmarks with highly technical content for LRLs and outline mitigation strategies. Our evaluation reveals a significant performance gap between proprietary models such as GPT-4o and o1-preview, and Claude models, and open-source models like Meta's LLaMA and Google's Gemma. Additionally, all models perform better in English than in African languages. These results indicate that LMs struggle with answering scientific questions and are more prone to generating false claims in low-resource African languages. Our findings underscore the necessity for continuous improvement of multilingual LM capabilities in LRL settings to ensure safe and reliable use in real-world contexts. We open-source the Uhura Benchmark and Uhura Platform to foster further research and development in NLP for LRLs.