Publications

Assessing Programming Task Difficulty for Efficient Evaluation of Large Language Models
Florian Tambon
Amin Nikanjam
Cyrine Zid
Foutse Khomh
Giuliano Antoniol
2025-10-27
ACM Transactions on Software Engineering and Methodology (publié)
doi.org
arxiv.org
Bridging Simulators with Conditional Optimal Transport
Justine Zeghal
Benjamin Remy
Yashar Hezaveh
François Lanusse
Laurence Perreault-Levasseur
2025-10-27
ArXiv (prépublication)
arxiv.org
arxiv.org
AfriMTEB and AfriE5: Benchmarking and Adapting Text Embedding Models for African Languages
Kosei Uemura
Miaoran Zhang
David Ifeoluwa Adelani
2025-10-26
ArXiv (prépublication)
doi.org
arxiv.org
Quantitative MRI of the hippocampus reveals microstructural trajectories of aging and Alzheimer’s disease pathology
Alfie Wearn
Christine L. Tardif
Ilana R. Leppert
Giulia Baracchini
Colleen Hughes
Jennifer Tremblay-Mercier
John Breitner
Judes Poirier
Sylvia Villeneuve
Boris C. Bernhardt
Gary R. Turner
R. Nathan Spreng
Sylvia Villeneuve
Judes Poirier
John Breitner
Sylvia Villeneuve
Andrée-Ann Baril
Pierre Bellec
Véronique Bohbot
Danilo Bzdok … (voir 27 de plus)
Mallar Chakravarty
D. Louis Collins
Mahsa Dadar
Simon Ducharme
Alan Evans
Claudine Gauthier
Maiya R. Geddes
Rick Hoge
Yasser Ituria-Medina
Gerhard Multhaup
Lisa-Marie Münter
Alexa Pichet Binette
Natasha Rajah
Pedro Rosa-Neto
Taylor Schmitz
Jean-Paul Soucy
R. Nathan Spreng
Christine L. Tardif
Etienne Vachon-Presseau
Christine L. Tardif
Maxime Descoteaux
Robert Laforce
Pierre Etienne
Serge Gauthier
Vasavan Nair
Judes Poirier
Daniel Auld
Hippocampal atrophy, typically measured using volumetry, is a hallmark feature of both normal aging and Alzheimer’s disease (AD). However,… (voir plus) the earliest stages of atrophy manifest as microstructural changes in tissue composition rather than macroscopic volume loss. We conducted longitudinal in vivo mapping of hippocampal microstructure in healthy aging and incipient AD, highlighting demyelination, iron deposition, and changes in water content as markers of age and AD risk. A combination of macrostructural and microstructural measures provides a more comprehensive picture of brain health and disease, unlocking unique insights into the pathological state of brain tissue and the impact of AD at a point where therapeutic rescue of the tissue is most likely to be efficacious.
2025-10-26
Proceedings of the National Academy of Sciences (publié)
doi.org
Deep-learning-based virtual screening of antibacterial compounds
Gabriele Scalia
Steven T. Rutherford
Ziqing Lu
Kerry R. Buchholz
Nicholas Skelton
Kangway Chuang
Nathaniel Diamant
Jan-Christian Hütter
Jerome-Maxim Luescher
Anh Miu
Jeff Blaney
Leo Gendelev
Elizabeth Skippington
Greg Zynda
Nia Dickson
Michał Koziarski
Yoshua Bengio
Aviv Regev
Man-Wah Tan
Tommaso Biancalani
2025-10-23
Nature Biotechnology (inconnu)
doi.org
Generalised Flow Maps for Few-Step Generative Modelling on Riemannian Manifolds
Oscar Davis
Michael S. Albergo
Nicholas Matthew Boffi
Michael M. Bronstein
Avishek Bose
2025-10-23
ArXiv (prépublication)
doi.org
arxiv.org
REVE: A Foundation Model for EEG -- Adapting to Any Setup with Large-Scale Pretraining on 25,000 Subjects
Yassine El Ouahidi
Jonathan Lys
Philipp Thölke
Nicolas Farrugia
Bastien Pasdeloup
Vincent Gripon
Karim Jerbi CoCo Lab
Giulia Lioi
2025-10-23
ArXiv (prépublication)
doi.org
arxiv.org
Surrogate-based quantification of policy uncertainty in generative flow networks
Ram'on Nartallo-Kaluarachchi
Robert Manson-Sawko
Shashanka Ubaru
Dongsung Huh
Malgorzata J. Zimo'n
Lior Horesh
Yoshua Bengio
2025-10-23
ArXiv (prépublication)
doi.org
arxiv.org
Generative Point Tracking with Flow Matching
Mattie Tesfaldet
Adam W. Harley
Konstantinos G. Derpanis
D. Nowrouzezahrai
Christopher Pal
Tracking a point through a video can be a challenging task due to uncertainty arising from visual obfuscations, such as appearance changes a… (voir plus)nd occlusions. Although current state-of-the-art discriminative models excel in regressing long-term point trajectory estimates -- even through occlusions -- they are limited to regressing to a mean (or mode) in the presence of uncertainty, and fail to capture multi-modality. To overcome this limitation, we introduce Generative Point Tracker (GenPT), a generative framework for modelling multi-modal trajectories. GenPT is trained with a novel flow matching formulation that combines the iterative refinement of discriminative trackers, a window-dependent prior for cross-window consistency, and a variance schedule tuned specifically for point coordinates. We show how our model's generative capabilities can be leveraged to improve point trajectory estimates by utilizing a best-first search strategy on generated samples during inference, guided by the model's own confidence of its predictions. Empirically, we evaluate GenPT against the current state of the art on the standard PointOdyssey, Dynamic Replica, and TAP-Vid benchmarks. Further, we introduce a TAP-Vid variant with additional occlusions to assess occluded point tracking performance and highlight our model's ability to capture multi-modality. GenPT is capable of capturing the multi-modality in point trajectories, which translates to state-of-the-art tracking accuracy on occluded points, while maintaining competitive tracking accuracy on visible points compared to extant discriminative point trackers.
2025-10-22
ArXiv (prépublication)
doi.org
arxiv.org
High IL1R1 expression predicts poor survival and benefit from stem cell transplant in intermediate-risk acute myeloid leukemia from the Leucegene cohort
Guillaume Richard-Carpentier
Francois Béliveau
Sandrine Lacoste
Banafsheh Khakipoor
Véronique Lisi
Michael Vladovsky
Miriam Marquis
Jean-François Spinella
Patrick Gendron
Sébastien Lemieux
Vincent-Philippe Lavallee
Guy Sauvageau
Josée Hébert
There is an unmet clinical need to identify patients with acute myeloid leukemia and intermediate-risk cytogenetics who benefit from allogen… (voir plus)eic hematopoietic stem cell transplantation in first remission, especially among those without FLT3 -ITD mutation. We analyzed transcriptomic data from the Leucegene cohort composed of 316 patients with acute myeloid leukemia and intermediate-risk cytogenetics who have been treated with intensive chemotherapy. We evaluated associations between gene expression and overall survival or relapse-free survival and we analyzed the interaction between gene expression and allogeneic hematopoietic stem cell transplantation to identify biomarkers that predict the benefit of stem cell transplantation in this subgroup of patients. We identified high IL1R1 expression ( IL1R1 high ) as a prognostic and predictive marker in the Leucegene cohort. IL1R1 high (≥ 2.0 transcripts per million) was associated with older age, monocytic differentiation, higher frequency of FLT3 -ITD and RUNX1 mutations and lower frequency of IDH1 / 2 and bZIP CEBPA mutations. Patients with IL1R1 high had lower 5-year overall survival (10% vs 38%, p  < 0.01), and higher 5-year cumulative incidence of relapse (76% vs 59%, p  < 0.01) than those with low IL1R1 expression. IL1R1 high was independently associated with overall survival in multivariable analyses including age, white blood cell count at diagnosis and NPM1 , FLT3 -ITD, bZIP CEBPA , RUNX1 , ASXL1 and DNMT3A mutations (HR 1.78, p  < 0.01). Importantly, in landmark analysis, hematopoietic stem cell transplantation in first remission significantly improved 5-year overall survival in patients with IL1R1 high (67% vs 27%, HR 0.33, p  < 0.01), but not in patients with IL1R1 low (62% vs 54%, HR 0.72, p  = 0.31), especially among those without FLT3 -ITD mutation (48% vs 50%, HR 0.93, p  = 0.85). In patients who proceeded to allogeneic hematopoietic stem cell transplantation, the 5-year overall survival was 60% in patients with IL1R1 high compared to 56% in patients with IL1R1 low confirming that the worse prognosis associated with high expression of IL1R1 was abrogated by stem cell transplantation. IL1R1 expression is a candidate marker to identify patients with intermediate-risk cytogenetics acute myeloid leukemia at high risk of relapse who benefit from allogeneic hematopoietic stem cell transplantation in first remission.
2025-10-22
Biomarker Research (publié)
doi.org
The Intermodal Railroad Blocking and Railcar Fleet-Management Planning Problem
Julie Kienzle
Serge Bisaillon
T. Crainic
Emma Frejinger
Rail is a cost-effective and relatively low-emission mode for transporting intermodal containers over long distances. This paper addresses t… (voir plus)actical planning of intermodal railroad operations by introducing a new problem that simultaneously considers three consolidation processes and the management of a heterogeneous railcar fleet. We model the problem with a scheduled service network design with resource management (SSND-RM) formulation, expressed as an integer linear program. While such formulations are challenging to solve at scale, we demonstrate that our problem can be tackled with a general-purpose solver when provided with high-quality warm-start solutions. To this end, we design a construction heuristic inspired by a relax-and-fix procedure. We evaluate the methodology on realistic, large-scale instances from our industrial partner, the Canadian National Railway Company: a North American Class I railroad. The computational experiments show that the proposed approach efficiently solves practically relevant instances, and that solutions to the SSND-RM formulation yield substantially more accurate capacity estimations compared to those obtained from simpler baseline models. Managerial insights from our study highlight that ignoring railcar fleet management or container loading constraints can lead to a severe underestimation of required capacity, which may result in costly operational inefficiencies. Furthermore, our results show that the use of multi-platform railcars improves overall capacity utilization and benefits the network, even if they can locally lead to less efficient loading as measured by terminal-level slot utilization performance indicators.
2025-10-22
ArXiv (prépublication)
arxiv.org
arxiv.org
BugPilot: Complex Bug Generation for Efficient Learning of SWE Skills
Atharv Sonwane
Isadora White
Hyunji Lee
Matheus Pereira
Lucas Caccia
Minseon Kim
Zhengyan Shi
Chinmay Singh
Alessandro Sordoni
Marc-Alexandre Côté
Xingdi Yuan
2025-10-21
ArXiv (prépublication)
doi.org
arxiv.org