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Publication search results
found 53 matches
- 2024
- Tuan Dung Lai
, Anj Simmons
, Scott Barnett
, Jean-Guy Schneider
, Rajesh Vasa
:
Comparative analysis of real issues in open-source machine learning projects. Empir. Softw. Eng. 29(3): 60 (2024) - Zafaryab Rasool
, Stefanus Kurniawan, Sherwin Balugo, Scott Barnett, Rajesh Vasa, Courtney Chesser, Benjamin M. Hampstead, Sylvie Belleville, Kon Mouzakis, Alex Bahar-Fuchs:
Evaluating LLMs on document-based QA: Exact answer selection and numerical extraction using CogTale dataset. Nat. Lang. Process. J. 8: 100083 (2024) - Hala Abdelkader
, Mohamed Abdelrazek
, Scott Barnett
, Jean-Guy Schneider
, Priya Rani
, Rajesh Vasa
:
ML-On-Rails: Safeguarding Machine Learning Models in Software Systems - A Case Study. CAIN 2024: 178-183 - Scott Barnett
, Stefanus Kurniawan
, Srikanth Thudumu
, Zach Brannelly
, Mohamed Abdelrazek
:
Seven Failure Points When Engineering a Retrieval Augmented Generation System. CAIN 2024: 194-199 - Jai Kannan
, Scott Barnett
, Anj Simmons
, Taylan Selvi
, Luis Cruz
:
Green Runner: A Tool for Efficient Deep Learning Component Selection. CAIN 2024: 112-117 - Zafaryab Rasool
, Scott Barnett
, David Willie
, Stefanus Kurniawan
, Sherwin Balugo
, Srikanth Thudumu
, Mohamed Abdelrazek
:
LLMs for Test Input Generation for Semantic Applications. CAIN 2024: 160-165 - Scott Barnett, Stefanus Kurniawan, Srikanth Thudumu, Zach Brannelly, Mohamed Abdelrazek:
Seven Failure Points When Engineering a Retrieval Augmented Generation System. CoRR abs/2401.05856 (2024) - Hala Abdelkader
, Mohamed Abdelrazek, Scott Barnett, Jean-Guy Schneider, Priya Rani, Rajesh Vasa:
ML-On-Rails: Safeguarding Machine Learning Models in Software Systems A Case Study. CoRR abs/2401.06513 (2024) - Zafaryab Rasool, Scott Barnett, David Willie, Stefanus Kurniawan, Sherwin Balugo, Srikanth Thudumu, Mohamed Almorsy Abdelrazek:
LLMs for Test Input Generation for Semantic Caches. CoRR abs/2401.08138 (2024) - Shangeetha Sivasothy, Scott Barnett, Rena Logothetis, Mohamed Abdelrazek, Zafaryab Rasool, Srikanth Thudumu, Zach Brannelly:
Large language models for generating rules, yay or nay? CoRR abs/2406.06835 (2024) - Scott Barnett, Zach Brannelly, Stefanus Kurniawan, Sheng Wong:
Fine-Tuning or Fine-Failing? Debunking Performance Myths in Large Language Models. CoRR abs/2406.11201 (2024) - Talia Gershon, Seetharami Seelam, Brian Belgodere, Milton Bonilla, Lan Hoang, Danny Barnett, I-Hsin Chung, Apoorve Mohan, Ming-Hung Chen, Lixiang Luo, Robert Walkup, Constantinos Evangelinos, Shweta Salaria, Marc Dombrowa, Yoonho Park, Apo Kayi, Liran Schour, Alim Alim, Ali Sydney, Pavlos Maniotis, Laurent Schares, Bernard Metzler, Bengi Karacali-Akyamac, Sophia Wen, Tatsuhiro Chiba, Sunyanan Choochotkaew, Takeshi Yoshimura, Claudia Misale, Tonia Elengikal, Kevin O. Connor, Zhuoran Liu, Richard Molina, Lars Schneidenbach, James Caden, Christopher Laibinis, Carlos Fonseca, Vasily Tarasov, Swaminathan Sundararaman, Frank B. Schmuck, Scott Guthridge, Jeremy Cohn, Marc Eshel, Paul Muench, Runyu Liu, William Pointer, Drew Wyskida, Bob Krull, Ray Rose, Brent Wolfe, William Cornejo, John Walter, Colm Malone, Clifford Perucci, Frank Franco, Nigel Hinds, Bob Calio, Pavel Druyan, Robert Kilduff, John Kienle, Connor McStay, Andrew Figueroa, Matthew Connolly, Edie Fost, Gina Roma, Jake Fonseca, Ido Levy, Michele Payne, Ryan Schenkel, Amir Malki, Lion Schneider, Aniruddha Narkhede, Shekeba Moshref, Alexandra Kisin, Olga Dodin, Bill Rippon, Henry Wrieth, John Ganci, Johnny Colino, Donna Habeger-Rose, Rakesh Pandey, Aditya Gidh, Aditya Gaur, Dennis Patterson, Samsuddin Salmani, Rambilas Varma, Rumana Rumana, Shubham Sharma, Mayank Mishra, Rameswar Panda, Aditya Prasad, Matt Stallone, Gaoyuan Zhang, Yikang Shen, David Cox, Ruchir Puri, Dakshi Agrawal, Drew Thorstensen, Joel Belog, Brent Tang:
The infrastructure powering IBM's Gen AI model development. CoRR abs/2407.05467 (2024) - 2023
- Ben Joseph Philip
, Mohamed Almorsy Abdelrazek
, Scott Barnett
, Alessio Bonti, John Grundy
:
Toward a Unified mHealth Platform: A Survey of Current User Challenges and Expectations. IEEE Access 11: 19876-19891 (2023) - Sheng Wong
, Anj Simmons
, Jessica Rivera-Villicana
, Scott Barnett
:
Estimating Patient-Level Uncertainty in Seizure Detection Using Group-Specific Out-of-Distribution Detection Technique. Sensors 23(20): 8375 (2023) - Hung Du, Srikanth Thudumu
, Sankhya Singh, Scott Barnett, Irini Logothetis, Rajesh Vasa
, Kon Mouzakis:
Decentralized Federated Learning Strategy with Image Classification using ResNet Architecture. CCNC 2023: 706-707 - Ben Joseph Philip, Yasmeen Anjeer Alshehhi, Mohamed Abdelrazek, Scott Barnett, Alessio Bonti, John Grundy:
mHealthSwarm: A Unified Platform for mHealth Applications. ENASE 2023: 605-612 - Tamal Mondal, Scott Barnett, Akash Lal, Jyothi Vedurada:
Cell2Doc: ML Pipeline for Generating Documentation in Computational Notebooks. ASE 2023: 384-396 - Sheng Wong, Scott Barnett
, Jessica Rivera-Villicana
, Anj Simmons, Hala Abdelkader
, Jean-Guy Schneider, Rajesh Vasa:
MLGuard: Defend Your Machine Learning Model! SE4SafeML@SIGSOFT FSE 2023: 10-13 - Jai Kannan, Scott Barnett, Anj Simmons, Taylan Selvi, Luis Cruz:
Green Runner: A tool for efficient model selection from model repositories. CoRR abs/2305.16849 (2023) - Sheng Wong, Scott Barnett, Jessica Rivera-Villicana, Anj Simmons, Hala Abdelkader, Jean-Guy Schneider, Rajesh Vasa:
MLGuard: Defend Your Machine Learning Model! CoRR abs/2309.01379 (2023) - Zafaryab Rasool, Scott Barnett, Stefanus Kurniawan, Sherwin Balugo, Rajesh Vasa, Courtney Chesser, Alex Bahar-Fuchs:
Evaluating LLMs on Document-Based QA: Exact Answer Selection and Numerical Extraction using Cogtale dataset. CoRR abs/2311.07878 (2023) - 2022
- Venkatesh Potluri, Maulishree Pandey, Andrew Begel, Michael Barnett, Scott Reitherman:
CodeWalk: Facilitating Shared Awareness in Mixed-Ability Collaborative Software Development. ASSETS 2022: 20:1-20:16 - Hung Du, Srikanth Thudumu
, Sankhya Singh, Scott Barnett, Irini Logothetis, Rajesh Vasa
, Kon Mouzakis:
A Framework for Evaluating MRC Approaches with Unanswerable Questions. e-Science 2022: 435-436 - Irini Logothetis, Scott Barnett, Leonard Hoon
, Srikanth Thudumu
, Joseph Mathew, Carl Luckhoff, Gerard O'Reilly, David Collard, Rajesh Vasa
, Kon Mouzakis, Mark Fitzgerald:
PiMS: A Pre-ML Labelling Tool. e-Science 2022: 431-432 - Johnahan Van Zyl, Hung Du, Srikanth Thudumu
, Irini Logothetis, Scott Barnett, Rajesh Vasa
, Kon Mouzakis:
Subspace based Anomaly Detection Framework for Point Clouds. e-Science 2022: 316-325 - Jai Kannan, Scott Barnett
, Luis Cruz
, Anj Simmons, Akash Agarwal:
MLSmellHound: A Context-Aware Code Analysis Tool. ICSE (NIER) 2022: 66-70 - Ben Joseph Philip
, Mohamed Abdelrazek, Scott Barnett
, Alessio Bonti, John C. Grundy:
Towards Better mHealth Apps: Understanding Current Challenges and User Expectations. MOBILESoft 2022: 33-37 - Jai Kannan, Scott Barnett, Luís Cruz, Anj Simmons, Akash Agarwal:
MLSmellHound: A Context-Aware Code Analysis Tool. CoRR abs/2205.03790 (2022) - Tuan Dung Lai, Anj Simmons, Scott Barnett, Jean-Guy Schneider, Rajesh Vasa:
Comparative analysis of real bugs in open-source Machine Learning projects - A Registered Report. CoRR abs/2209.09932 (2022) - 2021
- Jennifer Merrill, Scott Fogle, Holly K. Boyle, Nancy Barnett, Kate Carey:
Piloting the Alcohol Feedback, Reflection, and Morning Evaluation (A-FRAME) Program : A Smartphone-delivered Alcohol Intervention. HICSS 2021: 1-10
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