Accepted Lightning Talks

• 01
  MDSD: Multi-turn Diverse Synthetic Dialog Generation for Domain Specific Incomplete Requests Understanding

  Xi Li* (Apple), Xiaoxu Wu (Apple), Lijuan Xiao (Apple), Tao Liu (Apple), Ping Huang (Apple), Jiulong Shan (Apple)
• 02
  Model Slicing: a Data Engineering Perspective

  Parke Godfrey (York University), Lukasz Golab* (University of Waterloo), Divesh Srivastava (AT&T Chief Data Office), Jarek Szlichta (York University)
• 03
  Responsible Entity Resolution over Streaming Data

  Kostas Stefanidis* (Tampere University), Vasilis Efthymiou (Harokopio University of Athens), Tiago Brasileiro Araújo (Tampere University)
• 04
  Tuning IBM Db2 with Explainable AI

  Andrew Chai* (York University and IBM CAS), Alexander Bianchi (IBM Canada Ltd.), Vincent Corvinelli (IBM Canada Ltd.), Parke Godfrey (York University and IBM CAS), Lukasz Golab (University of Waterloo), Jarek Szlichta (York University and IBM CAS), Calisto Zuzarte (IBM Canada Ltd.)
• 05
  From Polystores to PolyDBMS: The Polypheny Experience

  Marco Vogt* (University of Basel), David Lengweiler (University of Basel), Martin Vahlensieck (University of Basel), Yiming Wu (University of Basel), Heiko Schuldt (University of Basel)
• 06
  Recovering Structure in Unstructured LLM Outputs

  Joel Rorseth* (University of Waterloo), Parke Godfrey (York University), Lukasz Golab (University of Waterloo), Divesh Srivastava (AT&T Chief Data Office), Szlichta Szlichta (York University)
• 07
  Rethinking BFT Consensus via Transaction-Level Protocol Construction for Optimal Performance

  BINGXU ZHU* (Concordia University), Gengrui Zhang (Concordia University)
• 08
  SENTINEL: Evaluating Pipeline Robustness to Distributional Shifts

  Jahid Hasan* (Purdue University), Jingya Wang (Purdue University), Romila Pradhan (Purdue University)
• 09
  SPLICE: An Efficient Framework for Selecting Sources for Machine Learning Tasks

  Ambarish Singh* (Purdue University), Romila Pradhan (Purdue University)
• 10
  When Text-to-SQL Evaluation Misleads: Rethinking Benchmarking Practices

  Oktie Hassanzadeh* (IBM Research), Nhan Pham (IBM Research), Timothy Dinger (IBM Research), Tanvi Kaple (IBM Research), Long Vu (IBM Research), Michael Glass (IBM Research), Shankar Subramanian (IBM Research)
• 11
  Are Dedicated Vector Databases Necessary? Benchmarking Vector Search in Relational and Analytical Systems for Enterprise Workloads

  Archan Dutta* (Aisera), Thais Poi (San Joaquin Delta College)
• 12
  Is Quantum Computing Ready for Real-Time Database Optimization?

  Hanwen Liu* (University of Southern California), Ibrahim Sabek (University of Southern California)
• 13
  On Breaking the Scalability Barrier in Data Cleaning

  El Kindi Rezig* (University of Utah)
• 14
  GNN Explainers 2.0: A Paradigm for User-Oriented, Data-Guided Explanations

  Arijit Khan* (Bowling Green State University)
• 15
  SalesforceDB: Built on one LSM to rule them all !

  Vaibhav Arora* (Salesforce)