ICSME 2023 (series) / New Ideas and Emerging Results Track /
Benchmarking Causal Study to Interpret Large Language Models for Source Code
Wed 4 Oct 2023 11:18 - 11:29 at Session 1 Room - RGD 004 - Machine Learning Applications Chair(s): Masud Rahman
Wed 4 OctDisplayed time zone: Bogota, Lima, Quito, Rio Branco change
Wed 4 Oct
Displayed time zone: Bogota, Lima, Quito, Rio Branco change
10:30 - 12:00 | Machine Learning ApplicationsResearch Track / Industry Track / New Ideas and Emerging Results Track at Session 1 Room - RGD 004 Chair(s): Masud Rahman Dalhousie University | ||
10:30 16mTalk | GPTCloneBench: A comprehensive benchmark of semantic clones and cross-language clones using GPT-3 model and SemanticCloneBench Research Track Ajmain Inqiad Alam University of Saskatchewan, Palash Ranjan Roy University of Saskatchewan, Farouq Al-omari University of Saskatchewan, Chanchal K. Roy University of Saskatchewan, Banani Roy University of Saskatchewan, Kevin Schneider University of Saskatchewan Pre-print | ||
10:46 16mTalk | DeltaNN: Assessing the Impact of Computational Environment Parameters on the Performance of Image Recognition Models Industry Track Nikolaos Louloudakis University of Edinburgh, Perry Gibson University of Glasgow, José Cano University of Glasgow, Ajitha Rajan University of Edinburgh | ||
11:02 16mTalk | You Augment Me: Exploring ChatGPT-based Data Augmentation for Semantic Code Search Research Track Yanlin Wang Sun Yat-sen University, Lianghong Guo Beijing University of Posts and Telecommunications, Ensheng Shi Xi’an Jiaotong University, Wenqing Chen Sun Yat-sen University, Jiachi Chen Sun Yat-sen University, Wanjun Zhong Sun Yat-sen University, Menghan Wang eBay Inc., Hui Li Xiamen University, Ziyu Lyu Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Hongyu Zhang Chongqing University, Zibin Zheng Sun Yat-sen University | ||
11:18 11mTalk | Benchmarking Causal Study to Interpret Large Language Models for Source Code New Ideas and Emerging Results Track Daniel Rodriguez-Cardenas , David Nader Palacio William and Mary, Dipin Khati William & Mary, Henry Burke William & Mary, Denys Poshyvanyk William & Mary | ||
11:29 16mTalk | Deploying Deep Reinforcement Learning Systems: A Taxonomy of Challenges Research Track Ahmed Haj Yahmed École Polytechnique de Montréal, Altaf Allah Abbassi Polytechnique Montreal, Amin Nikanjam École Polytechnique de Montréal, Heng Li Polytechnique Montréal, Foutse Khomh Polytechnique Montréal | ||
11:45 15mLive Q&A | 1:1 Q&A Research Track | ||