Wed 6 Dec 2023 14:15 - 14:22 at Golden Gate C2 - Machine Learning III Chair(s): Rangeet Pan

This tool demonstration presents a research toolkit for a language model of Java source code. The target audience includes researchers studying problems at the granularity level of subroutines, statements, or variables in Java. In contrast to many existing language models, we prioritize features for researchers including an open and easily-searchable training set, a held out test set with different levels of deduplication from the training set, infrastructure for deduplicating new examples, and an implementation platform suitable for execution on equipment accessible to a relatively modest budget. Our model is a GPT2-like architecture with 350m parameters. Our training set includes 52m Java methods (9b tokens) and 13m StackOverflow threads (10.5b tokens). To improve accessibility of research to more members of the community, we limit local resource requirements to GPUs with 16GB video memory. We provide a test set of held out Java methods that include descriptive comments, including the entire Java projects for those methods. We also provide deduplication tools using precomputed hash tables at various similarity thresholds to help researchers ensure that their own test examples are not in the training set. We make all our tools and data open source and available via Huggingface and Github.

Wed 6 Dec

Displayed time zone: Pacific Time (US & Canada) change

14:00 - 15:30
Machine Learning IIIDemonstrations / Industry Papers / Research Papers at Golden Gate C2
Chair(s): Rangeet Pan IBM Research
14:00
15m
Talk
Benchmarking Robustness of AI-enabled Multi-sensor Fusion Systems: Challenges and Opportunities
Research Papers
Xinyu Gao , Zhijie Wang University of Alberta, Yang Feng Nanjing University, Lei Ma The University of Tokyo / University of Alberta, Zhenyu Chen Nanjing University, Baowen Xu Nanjing University
Media Attached
14:15
7m
Talk
A Language Model of Java Methods with Train/Test Deduplication
Demonstrations
Chia-Yi Su University of Notre Dame, Aakash Bansal University of Notre Dame, Vijayanta Jain University of Maine, Sepideh Ghanavati University of Maine , Collin McMillan University of Notre Dame
Media Attached
14:23
7m
Talk
DENT - A Tool for Tagging Stack Overflow Posts With Deep Learning Energy Patterns
Demonstrations
Shriram Shanbhag Indian Institute of Technology Tirupati, Sridhar Chimalakonda Indian Institute of Technology Tirupati, Vibhu Saujanya Sharma Accenture Labs, India, Vikrant Kaulgud Accenture Labs, India
Media Attached
14:30
15m
Talk
Automated Testing and Improvement of Named Entity Recognition Systems
Research Papers
BoXi Yu The Chinese University of Hong Kong, Shenzhen, Yiyan Hu The Chinese University of Hong Kong, Shenzhen, Qiuyang Mang The Chinese University of Hong Kong, Shenzhen, Wenhan Hu The Chinese University of Hong Kong, Shenzhen, Pinjia He The Chinese University of Hong Kong, Shenzhen
Pre-print Media Attached
14:45
15m
Talk
KDDT: Knowledge Distillation-Empowered Digital Twin for Anomaly Detection
Industry Papers
Xu Qinghua Simula Research Laboratory; University of Oslo, Shaukat Ali Simula Research Laboratory and Oslo Metropolitan University, Tao Yue Beihang University, Zaimovic Nedim Alstom Rail, Inderjeet Singh Alstom
DOI Media Attached
15:00
15m
Talk
Deep Learning Based Feature Envy Detection Boosted by Real-World Examples
Research Papers
Bo Liu Beijing Institute of Technology, Hui Liu Beijing Institute of Technology, Guangjie Li National Innovation Institute of Defense Technology, Nan Niu University of Cincinnati, Zimao Xu Beijing Institute of Technology, Yifan Wang Huawei Cloud, Yunni Xia Chongqing University, Yuxia Zhang Beijing Institute of Technology, Yanjie Jiang Peking University
DOI Pre-print Media Attached
15:15
15m
Talk
[Remote] The EarlyBIRD Catches the Bug: On Exploiting Early Layers of Encoder Models for More Efficient Code Classification
Research Papers
Anastasiia Grishina Simula Research Laboratory, Max Hort Simula Research Laboratory, Leon Moonen Simula Research Laboratory and BI Norwegian Business School
Pre-print Media Attached