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ORCIDGUIDE-AI@SIGMOD 2024: Santiago, Chile
- Proceedings of the Conference on Governance, Understanding and Integration of Data for Effective and Responsible AI, GUIDE-AI 2024, Santiago, Chile, June 9-15, 2024. ACM 2024
- Anna Zeng
, Mike Cafarella:
Digging Up Threats to Validity: A Data Marshalling Approach to Sensitivity Analysis. 1-5 - Markos Markakis, Ziyu Zhang, Rana Shahout, Trinity Gao, Chunwei Liu, Ibrahim Sabek, Michael J. Cafarella:
Press ECCS to Doubt (Your Causal Graph). 6-15 - Yanlin Feng, Sajjadur Rahman, Aaron Feng, Vincent Chen, Eser Kandogan:
CMDBench: A Benchmark for Coarse-to-fine Multimodal Data Discovery in Compound AI Systems. 16-25 - Jiaxiang Liu, Zezhou Huang, Eugene Wu:
SET: Searching Effective Supervised Learning Augmentations in Large Tabular Data Repositories. 26-31 - Leopoldo E. Bertossi, Felipe Azúa:
The Generalized Causal-Effect Score in Data Management (short paper). 32-35 - Zezhou Huang:
Disambiguate Entity Matching using Large Language Models through Relation Discovery. 36-39 - Mohammad Hossein Moslemi, Mostafa Milani:
Threshold-Independent Fair Matching through Score Calibration. 40-44 - Yael Einy, Tova Milo, Slava Novgorodov:
Cost-Effective LLM Utilization for Machine Learning Tasks over Tabular Data. 45-49 - Armin Esmaeilzadeh, Joel Rorseth, Andy Yu, Parke Godfrey, Lukasz Golab, Divesh Srivastava, Jaroslaw Szlichta, Kazem Taghva:
On Integrating the Data-Science and Machine-Learning Pipelines for Responsible AI. 50-53 - Amirhossein Aminimehr, Pouya Khani, Amirali Molaei, Amirmohammad Kazemeini, Erik Cambria:
TbExplain: A Text-Based Explanation Method for Scene Classification Models With the Statistical Prediction Correction. 54-60
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