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ORCIDAnthony Sicilia
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2020 – today
- 2024
[c14]Anthony Sicilia, Hyunwoo Kim, Khyathi Raghavi Chandu, Malihe Alikhani, Jack Hessel:
Deal, or no deal (or who knows)? Forecasting Uncertainty in Conversations using Large Language Models. ACL (Findings) 2024: 11700-11726- [c13]Katherine Atwell, Mert Inan, Anthony B. Sicilia, Malihe Alikhani:
Combining Discourse Coherence with Large Language Models for More Inclusive, Equitable, and Robust Task-Oriented Dialogue. LREC/COLING 2024: 3538-3552 - [c12]Anthony Sicilia, Jennifer C. Gates, Malihe Alikhani:
HumBEL: A Human-in-the-Loop Approach for Evaluating Demographic Factors of Language Models in Human-Machine Conversations. EACL (1) 2024: 1127-1143 - [c11]Mert Inan, Katherine Atwell, Anthony Sicilia, Lorna C. Quandt, Malihe Alikhani:
Generating Signed Language Instructions in Large-Scale Dialogue Systems. NAACL (Industry Track) 2024: 140-154 - [i12]Anthony Sicilia, Hyunwoo Kim, Khyathi Raghavi Chandu, Malihe Alikhani, Jack Hessel:
Deal, or no deal (or who knows)? Forecasting Uncertainty in Conversations using Large Language Models. CoRR abs/2402.03284 (2024) - 2023
- [j2]Anthony Sicilia, Xingchen Zhao, Seong Jae Hwang
:
Domain adversarial neural networks for domain generalization: when it works and how to improve. Mach. Learn. 112(7): 2685-2721 (2023) - [c10]Anthony Sicilia, Malihe Alikhani:
Learning to Generate Equitable Text in Dialogue from Biased Training Data. ACL (1) 2023: 2898-2917 - [i11]Anthony Sicilia, Jennifer C. Gates, Malihe Alikhani:
How Old is GPT?: The HumBEL Framework for Evaluating Language Models using Human Demographic Data. CoRR abs/2305.14195 (2023) - [i10]Anthony Sicilia, Malihe Alikhani:
Learning to Generate Equitable Text in Dialogue from Biased Training Data. CoRR abs/2307.04303 (2023) - 2022
- [j1]Anthony Sicilia, Tristan Maidment, Pat Healy, Malihe Alikhani:
Modeling Non-Cooperative Dialogue: Theoretical and Empirical Insights. Trans. Assoc. Comput. Linguistics 10: 1084-1102 (2022) - [c9]Katherine Atwell, Anthony Sicilia, Seong Jae Hwang, Malihe Alikhani:
The Change that Matters in Discourse Parsing: Estimating the Impact of Domain Shift on Parser Error. ACL (Findings) 2022: 824-845 - [c8]Xingchen Zhao, Chang Liu, Anthony Sicilia, Seong Jae Hwang, Yun Fu:
Test-time Fourier Style Calibration for Domain Generalization. IJCAI 2022: 1721-1727 - [c7]Anthony Sicilia, Malihe Alikhani:
LEATHER: A Framework for Learning to Generate Human-like Text in Dialogue. AACL/IJCNLP (Findings) 2022: 30-53 - [c6]Anthony Sicilia, Katherine Atwell, Malihe Alikhani, Seong Jae Hwang:
PAC-Bayesian domain adaptation bounds for multiclass learners. UAI 2022: 1824-1834 - [i9]Katherine Atwell, Anthony Sicilia, Seong Jae Hwang, Malihe Alikhani:
The Change that Matters in Discourse Parsing: Estimating the Impact of Domain Shift on Parser Error. CoRR abs/2203.11317 (2022) - [i8]Xingchen Zhao, Chang Liu, Anthony Sicilia, Seong Jae Hwang, Yun Fu:
Test-time Fourier Style Calibration for Domain Generalization. CoRR abs/2205.06427 (2022) - [i7]Anthony Sicilia, Katherine Atwell, Malihe Alikhani, Seong Jae Hwang:
PAC-Bayesian Domain Adaptation Bounds for Multiclass Learners. CoRR abs/2207.05685 (2022) - [i6]Anthony Sicilia, Tristan Maidment, Pat Healy, Malihe Alikhani:
Modeling Non-Cooperative Dialogue: Theoretical and Empirical Insights. CoRR abs/2207.07255 (2022) - [i5]Anthony Sicilia, Malihe Alikhani:
LEATHER: A Framework for Learning to Generate Human-like Text in Dialogue. CoRR abs/2210.07777 (2022) - 2021
- [c5]Anthony Sicilia, Xingchen Zhao, Davneet S. Minhas, Erin O'Connor, Howard J. Aizenstein, William E. Klunk, Dana L. Tudorascu, Seong Jae Hwang:
Multi-Domain Learning By Meta-Learning: Taking Optimal Steps In Multi-Domain Loss Landscapes By Inner-Loop Learning. ISBI 2021: 650-654 - [c4]Xingchen Zhao, Anthony Sicilia, Davneet S. Minhas, Erin O'Connor, Howard J. Aizenstein, William E. Klunk, Dana L. Tudorascu, Seong Jae Hwang:
Robust White Matter Hyperintensity Segmentation On Unseen Domain. ISBI 2021: 1047-1051 - [c3]Anthony Sicilia, Xingchen Zhao, Anastasia Sosnovskikh, Seong Jae Hwang:
PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging. MICCAI (3) 2021: 560-570 - [i4]Anthony Sicilia, Xingchen Zhao, Seong Jae Hwang:
Domain Adversarial Neural Networks for Domain Generalization: When It Works and How to Improve. CoRR abs/2102.03924 (2021) - [i3]Xingchen Zhao, Anthony Sicilia, Davneet S. Minhas, Erin O'Connor, Howard Aizenstein, William E. Klunk, Dana Tudorascu, Seong Jae Hwang:
Robust White Matter Hyperintensity Segmentation on Unseen Domain. CoRR abs/2102.06650 (2021) - [i2]Anthony Sicilia, Xingchen Zhao, Davneet S. Minhas, Erin O'Connor, Howard Aizenstein, William E. Klunk, Dana Tudorascu, Seong Jae Hwang:
Multi-Domain Learning by Meta-Learning: Taking Optimal Steps in Multi-Domain Loss Landscapes by Inner-Loop Learning. CoRR abs/2102.13147 (2021) - [i1]Anthony Sicilia, Xingchen Zhao, Anastasia Sosnovskikh, Seong Jae Hwang:
PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging. CoRR abs/2104.05600 (2021)
2010 – 2019
- 2019
- [c2]Anthony Sicilia, Konstantinos Pelechrinis, Kirk Goldsberry:
DeepHoops: Evaluating Micro-Actions in Basketball Using Deep Feature Representations of Spatio-Temporal Data. KDD 2019: 2096-2104 - 2018
- [c1]Mark Silvis, Anthony Sicilia, Alexandros Labrinidis:
PittGrub: A Frustration-Free System to Reduce Food Waste by Notifying Hungry College Students. KDD 2018: 754-763
Coauthor Index
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last updated on 2024-09-26 01:53 CEST by the dblp team
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