An Empirical Study on Low- and High-Level Explanations of Deep Learning Misbehaviours (ESEIW 2023 - ESEM Technical Papers Track) - ESEIW 2023

Sun 22 - Fri 27 October 2023 New Orleans, Louisiana, United States

Who

Tahereh Zohdinasab, Vincenzo Riccio, Paolo Tonella

Track

ESEIW 2023 ESEM Technical Papers

Time Zone

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When

Thu 26 Oct 2023 11:10 - 11:30 at Rhythms 3 - 1B - Machine learning in SE Chair(s): Davide Taibi

Tahereh Zohdinasab

USI Lugano

Switzerland

Vincenzo Riccio

University of Udine

Italy

Paolo Tonella

USI Lugano

Switzerland

Time Zone

The program is currently displayed in (GMT-05:00) Central Time (US & Canada).

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The GMT offsets shown reflect the offsets at the moment of the conference.

Time Band

By setting a time band, the program will dim events that are outside this time window. This is useful for (virtual) conferences with a continuous program (with repeated sessions).
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Session Program

Thu 26 Oct
Displayed time zone: Central Time (US & Canada) change

	10:30 - 12:15	1B - Machine learning in SEESEM Technical Papers / ESEM Journal-First Papers / ESEM IGC at Rhythms 3 Chair(s): Davide Taibi University of Oulu

	10:30 20m Full-paper		What is the Carbon Footprint of ML Models on Hugging Face? A Repository Mining Study ESEM Technical Papers Joel Castaño Fernández Universitat Politècnica de Catalunya (UPC), Silverio Martínez-Fernández UPC-BarcelonaTech, Xavier Franch Universitat Politècnica de Catalunya, Justus Bogner Vrije Universiteit Amsterdam Link to publication Pre-print
	10:50 20m Full-paper		An Exploratory Literature Study on Sharing and Energy Use of Language Models for Source Code ESEM Technical Papers Max Hort Simula Research Laboratory, Anastasiia Grishina Simula Research Laboratory, Leon Moonen Simula Research Laboratory and BI Norwegian Business School Pre-print Media Attached
	11:10 20m Full-paper		An Empirical Study on Low- and High-Level Explanations of Deep Learning Misbehaviours ESEM Technical Papers Tahereh Zohdinasab USI Lugano, Vincenzo Riccio University of Udine, Paolo Tonella USI Lugano
	11:30 20m Full-paper		Assessing the Use of AutoML for Data-Driven Software Engineering ESEM Technical Papers Fabio Calefato University of Bari, Luigi Quaranta University of Bari, Italy, Filippo Lanubile University of Bari, Marcos Kalinowski Pontifical Catholic University of Rio de Janeiro (PUC-Rio) Pre-print
	11:50 10m Journal Early-Feedback		An Empirical Study on ML DevOps Adoption Trends, Efforts, and Benefits Analysis ESEM Journal-First Papers Dhia Elhaq Rzig University of Michigan - Dearborn, Foyzul Hassan University of Michigan at Dearborn, Marouane Kessentini Oakland University
	12:00 15m Industry talk		The Perspective of Software Professionals on Algorithmic Racism ESEM IGC Ronnie de Souza Santos University of Calgary, Luiz Fernando de Lima , Cleyton Vanut Cordeiro de Magalhães