arXiv:2606. 24407v1 Announce Type: cross Abstract: We consider an oracle that processes a limited batch of records at a time and clusters those that refer to the same real-world entity.
By Lorenzo Balzotti, Donatella Firmani, Luca Gagliardelli, Giovanni Simonini
arXiv:2607. 26298v1 Announce Type: new Abstract: We built and evaluated a self-serve entity resolution (ER) system on six benchmarks spanning 864 to 5M records, and three lessons emerged that are absent from existing ER literature.
By Kaushik Pavani, Ganga Aluri, Pravin Jadhav, Neeraj Prasad, Kiran Sanka
arXiv:2604. 26180v2 Announce Type: replace-cross Abstract: With recent semantic query processing engines, semantic aggregation has become a primitive operator, enabling the reduction of a relation into a natural language aggregate using an LLM.
By Alexander W. Lee, Benjamin Han, Shayak Sen, Sam Yeom, Ugur Cetintemel, Anupam Datta
arXiv:2607. 25135v1 Announce Type: new Abstract: Recent advances in RAG aim to optimize for performance by paying high ingestion costs for knowledge ingestion: building knowledge graphs or extracting SQL tables.
By Hilaf Hasson, Aditya Chakravarty, Jayant Thomas, Krishna Gogineni
arXiv:2607. 09236v1 Announce Type: new Abstract: Machine unlearning in LLMs is the targeted removal of specific knowledge while preserving all other capabilities, critical for privacy and safety.
By Amit Peleg, Naman Deep Singh, Naama Pearl, Bibhabasu Mohapatra, Matthias Hein
arXiv:2604. 00660v2 Announce Type: replace-cross Abstract: Modern data warehouses extend SQL with semantic operators that invoke large language models on each qualifying row, making per-row inference orders of magnitude more expensive than traditional SQL.
By Pawe{\l} Liskowski, Kyle Schmaus