Publications

MOSEAC: Streamlined Variable Time Step Reinforcement Learning
Yong Wang
Giovanni Beltrame
2024-06-02
ArXiv (prépublication)
doi.org
arxiv.org
Political Dynasties in Canada
Alex B. Rivard
Jean-François Godbout
Marc André Bodet
Using a unique dataset of legislators' electoral and biographical data in the Canadian provinces of Ontario, Quebec, New Brunswick, Nova Sco… (voir plus)tia and the federal parliament, this article analyses the extent to which family dynasties affected the career development of legislators since the mid-18th century. We find that the prevalence of dynasties was higher in provincial legislatures than it was in the federal parliament, that the number of dynasties in the Senate increased until the mid-20th century, and that the proportion of dynastic legislators at the subnational level was similar to the numbers seen in the United Kingdom during the early 19th century. Our results confirm the existence of a clear career benefit in terms of cabinet and senate appointments. In contrast to the American case and in line with the United Kingdom experience, we find no causal relationship between a legislator's tenure length and the presence of a dynasty.
2024-06-02
Government and Opposition (publié)
doi.org
AfriMTE and AfriCOMET: Enhancing COMET to Embrace Under-resourced African Languages
Jiayi Wang
David Ifeoluwa Adelani
Sweta Agrawal
Marek Masiak
Ricardo Rei
Eleftheria Briakou
Marine Carpuat
Xuanli He
Sofia Bourhim
Andiswa Bukula
Muhidin A. Mohamed
Temitayo Olatoye
Tosin Adewumi
Hamam Mokayed
Christine Mwase
Wangui Kimotho
Foutse Yuehgoh
Aremu Anuoluwapo
Jessica Ojo
Shamsuddeen Hassan Muhammad … (voir 41 de plus)
Salomey Osei
Abdul-Hakeem Omotayo
Chiamaka Ijeoma Chukwuneke
Perez Ogayo
Oumaima Hourrane
Salma El Anigri
Lolwethu Ndolela
Thabiso Mangwana
Shafie Abdi Mohamed
Hassan Ayinde
Ayinde Hassan
Oluwabusayo Olufunke Awoyomi
Lama Alkhaled
sana Sabah al-azzawi
Naome Etori
Millicent Ochieng
Clemencia Siro
Samuel Njoroge
Njoroge Kiragu
Eric Muchiri
Wangari Kimotho
Lyse Naomi Wamba
Daud Abolade
Simbiat Ajao
Iyanuoluwa Shode
Ricky Macharm
Ruqayya Nasir Iro
Saheed Salahudeen Abdullahi
Stephen Moore
Bernard Opoku
Zainab Akinjobi
Abeeb Afolabi
Nnaemeka Casmir Obiefuna
Onyekachi Ogbu
Sam Brian
Sam Ochieng’
Verrah Akinyi Otiende
CHINEDU EMMANUEL MBONU
Toadoum Sari Sakayo
Yao Lu
Pontus Stenetorp
Despite the recent progress on scaling multilingual machine translation (MT) to several under-resourced African languages, accurately measur… (voir plus)ing this progress remains challenging, since evaluation is often performed on n-gram matching metrics such as BLEU, which typically show a weaker correlation with human judgments. Learned metrics such as COMET have higher correlation; however, the lack of evaluation data with human ratings for under-resourced languages, complexity of annotation guidelines like Multidimensional Quality Metrics (MQM), and limited language coverage of multilingual encoders have hampered their applicability to African languages. In this paper, we address these challenges by creating high-quality human evaluation data with simplified MQM guidelines for error detection and direct assessment (DA) scoring for 13 typologically diverse African languages. Furthermore, we develop AfriCOMET: COMET evaluation metrics for African languages by leveraging DA data from well-resourced languages and an African-centric multilingual encoder (AfroXLM-R) to create the state-of-the-art MT evaluation metrics for African languages with respect to Spearman-rank correlation with human judgments (0.441).
2024-05-31
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) (publié)
doi.org
arxiv.org
Better entity matching with transformers through ensembles
Jwen Fai Low
Benjamin C. M. Fung
Pulei Xiong
2024-05-31
Knowledge-Based Systems (publié)
doi.org
Evaluating In-Context Learning of Libraries for Code Generation
Arkil Patel
Siva Reddy
Dzmitry Bahdanau
Pradeep Dasigi
2024-05-31
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) (publié)
doi.org
arxiv.org
Immunotherapeutic targeting of surfaceome heterogeneity in AML
Marie-Eve Bordeleau
Éric Audemard
Arnaud Metois
Louis Theret
Véronique Lisi
Azer Farah
Jean-François Spinella
Jalila Chagraoui
Ossama Moujaber
Léo Aubert
Banafsheh Khakipoor
Laure Mallinger
Isabel Boivin
Nadine Mayotte
Azadeh Hajmirza
Éric Bonneil
Francois Béliveau
Sybille Pfammatter
Albert Feghaly
Geneviève Boucher … (voir 9 de plus)
Patrick Gendron
Pierre Thibault
Frederic Barabe
Sébastien Lemieux
Guillaume Richard-Carpentier
Josée Hébert
Vincent-Philippe Lavallee
Philippe P. Roux
Guy Sauvageau
2024-05-31
Cell Reports (publié)
doi.org
Methods, Applications, and Directions of Learning-to-Rank in NLP Research
Justin Lee
Gabriel Bernier-Colborne
Tegan Maharaj
Sowmya Vajjala
Learning-to-rank (LTR) algorithms aim to order a set of items according to some criteria. They are at the core of applications such as web s… (voir plus)earch and social media recommendations, and are an area of rapidly increasing interest, with the rise of large language models (LLMs) and the widespread impact of these technologies on society. In this paper, we survey the diverse use cases of LTR methods in natural language processing (NLP) research, looking at previously under-studied aspects such as multilingualism in LTR applications and statistical significance testing for LTR problems. We also consider how large language models are changing the LTR landscape. This survey is aimed at NLP researchers and practitioners interested in understanding the formalisms and best practices regarding the application of LTR approaches in their research.
2024-05-31
Findings of the Association for Computational Linguistics: NAACL 2024 (publié)
doi.org
"One-Size-Fits-All"? Examining Expectations around What Constitute"Fair"or"Good"NLG System Behaviors
Li Lucy
Su Lin Blodgett
Milad Shokouhi
Hanna Wallach
A.R. Olteanu
Fairness-related assumptions about what constitute appropriate NLG system behaviors range from invariance, where systems are expected to beh… (voir plus)ave identically for social groups, to adaptation, where behaviors should instead vary across them. To illuminate tensions around invariance and adaptation, we conduct five case studies, in which we perturb different types of identity-related language features (names, roles, locations, dialect, and style) in NLG system inputs. Through these cases studies, we examine people's expectations of system behaviors, and surface potential caveats of these contrasting yet commonly held assumptions. We find that motivations for adaptation include social norms, cultural differences, feature-specific information, and accommodation; in contrast, motivations for invariance include perspectives that favor prescriptivism, view adaptation as unnecessary or too difficult for NLG systems to do appropriately, and are wary of false assumptions. Our findings highlight open challenges around what constitute"fair"or"good"NLG system behaviors.
2024-05-31
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) (publié)
doi.org
arxiv.org
PCR191 Patient-Centric Assessment of Treatment Experience in Breast Cancer: Development and Validation of a Patient Questionnaire
K. Gurjar
B. Rattanavong
L. Bennetts
J. Sahota
M. Ouerghi
C. Ammendolea
J. Asselah
S. Bartlett
C. Brezden-Masley
J. Croke
T. Hijal
J. Kildea
J. Papadakos
L. Watson
D. Soliman
2024-05-31
Value in Health (publié)
doi.org
Pioneering women in nuclear and radiation sciences
Mirta Dumancic
S. Enger
2024-05-31
Radiotherapy and Oncology (publié)
doi.org
Protocol to perform integrative analysis of high-dimensional single-cell multimodal data using an interpretable deep learning technique
Manqi Zhou
Hao Zhang
Zilong Bai
Dylan Mann-Krzisnik
Fei Wang
Yue Li
2024-05-31
STAR Protocols (publié)
doi.org
Reducing Two-Way Ranging Variance by Signal-Timing Optimization
Mohammed Ayman Shalaby
Charles Champagne Cossette
James Richard Forbes
Jerome Le Ny
Time-of-flight-based ranging among transceivers with different clocks requires protocols that accommodate varying rates of the clocks. Doubl… (voir plus)e-sided two-way ranging (DS-TWR) is widely adopted as a standard protocol due to its accuracy; however, the precision of DS-TWR has not been clearly addressed. In this paper, an analytical model of the variance of DS-TWR is derived as a function of the user-programmed response delays, which is then compared to the Cramer-Rao Lower Bound (CRLB). This is then used to formulate an optimization problem over the response delays in order to maximize the information gained from range measurements. The derived analytical variance model and optimized protocol are validated experimentally with 2 ranging UWB transceivers, where 29 million range measurements are collected.
2024-05-31
IEEE Transactions on Aerospace and Electronic Systems (publié)
doi.org
arxiv.org