no code implementations • 5 Feb 2024 • Anthony Sicilia, Hyunwoo Kim, Khyathi Raghavi Chandu, Malihe Alikhani, Jack Hessel
Effective interlocutors account for the uncertain goals, beliefs, and emotions of others.
1 code implementation • 10 Jul 2023 • Anthony Sicilia, Malihe Alikhani
Absence of equitable and inclusive principles can hinder the formation of common ground, which in turn negatively impacts the overall performance of the system.
1 code implementation • 23 May 2023 • Anthony Sicilia, Jennifer C. Gates, Malihe Alikhani
While demographic factors like age and gender change the way people talk, and in particular, the way people talk to machines, there is little investigation into how large pre-trained language models (LMs) can adapt to these changes.
3 code implementations • 14 Oct 2022 • Anthony Sicilia, Malihe Alikhani
From this insight, we propose a new algorithm, and empirically, we demonstrate our proposal improves both task-success and human-likeness of the generated text.
1 code implementation • 15 Jul 2022 • Anthony Sicilia, Tristan Maidment, Pat Healy, Malihe Alikhani
We use the tools of learning theory to develop a theoretical model for identifying non-cooperative interlocutors and apply this theory to analyze different communication strategies.
1 code implementation • 12 Jul 2022 • Anthony Sicilia, Katherine Atwell, Malihe Alikhani, Seong Jae Hwang
Multiclass neural networks are a common tool in modern unsupervised domain adaptation, yet an appropriate theoretical description for their non-uniform sample complexity is lacking in the adaptation literature.
1 code implementation • 13 May 2022 • Xingchen Zhao, Chang Liu, Anthony Sicilia, Seong Jae Hwang, Yun Fu
Thus, it is still possible that those methods can overfit to source domains and perform poorly on target domains.
4 code implementations • Findings (ACL) 2022 • Katherine Atwell, Anthony Sicilia, Seong Jae Hwang, Malihe Alikhani
Our results not only motivate our proposal and help us to understand its limitations, but also provide insight on the properties of discourse models and datasets which improve performance in domain adaptation.
1 code implementation • 12 Apr 2021 • Anthony Sicilia, Xingchen Zhao, Anastasia Sosnovskikh, Seong Jae Hwang
Application of deep neural networks to medical imaging tasks has in some sense become commonplace.
no code implementations • 25 Feb 2021 • Anthony Sicilia, Xingchen Zhao, Davneet Minhas, Erin O'Connor, Howard Aizenstein, William Klunk, Dana Tudorascu, Seong Jae Hwang
We consider a model-agnostic solution to the problem of Multi-Domain Learning (MDL) for multi-modal applications.
1 code implementation • 12 Feb 2021 • Xingchen Zhao, Anthony Sicilia, Davneet Minhas, Erin O'Connor, Howard Aizenstein, William Klunk, Dana Tudorascu, Seong Jae Hwang
That is, we train on samples from a set of distributions (sources) and test on samples from a new, unseen distribution (target).
1 code implementation • 7 Feb 2021 • Anthony Sicilia, Xingchen Zhao, Seong Jae Hwang
Further, this theory has been well-used in practice.