Kapil Vaidya - RankMe

19 papers A* 1A 1Journal 14Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	ODIN: A NL2SQL Recommender to Handle Schema Ambiguity. CoRR Kapil Vaidya, Abishek Sankararaman, Jialin Ding, Chuan Lei, Xiao Qin, Balakrishnan Narayanaswamy, Tim Kraska
2025	J	`jnl`	SQLens: An End-to-End Framework for Error Detection and Correction in Text-to-SQL. CoRR Yue Gong, Chuan Lei, Xiao Qin, Kapil Vaidya, Balakrishnan Narayanaswamy, Tim Kraska
2025	J	`jnl`	TailorSQL: An NL2SQL System Tailored to Your Query Workload. CoRR Kapil Vaidya, Jialin Ding, Sebastian Kosak, David Kernert, Chuan Lei, Xiao Qin, Abhinav Tripathy, Ramesh Balan, Balakrishnan Narayanaswamy, Tim Kraska
2025	—	`conf`	Utilizing Past User Feedback for More Accurate Text-to-SQL. HILDA@SIGMOD Matthias Urban, Jialin Ding, David Kernert, Kapil Vaidya, Tim Kraska
2024	A	`conf`	Panda: Performance Debugging for Databases using LLM Agents. CIDR Vikramank Y. Singh, Kapil Vaidya, Vinayshekhar Bannihatti Kumar, Sopan Khosla, Balakrishnan Narayanaswamy, Rashmi Gangadharaiah, Tim Kraska
2024	J	`jnl`	Why TPC Is Not Enough: An Analysis of the Amazon Redshift Fleet. Proc. VLDB Endow. Alexander van Renen, Dominik Horn, Pascal Pfeil, Kapil Vaidya, Wenjian Dong, Murali Narayanaswamy, Zhengchun Liu, Gaurav Saxena, Andreas Kipf, Tim Kraska
2023	—	`—`	Instance-Optimized Data Structures for Membership Queries Kapil Vaidya
2022	J	`jnl`	Can Learned Models Replace Hash Functions? Proc. VLDB Endow. Ibrahim Sabek, Kapil Vaidya, Dominik Horn, Andreas Kipf, Michael Mitzenmacher, Tim Kraska
2022	J	`jnl`	SNARF: A Learning-Enhanced Range Filter. Proc. VLDB Endow. Kapil Vaidya, Tim Kraska, Subarna Chatterjee, Eric R. Knorr, Michael Mitzenmacher, Stratos Idreos
2022	J	`jnl`	SageDB: An Instance-Optimized Data Analytics System. Proc. VLDB Endow. Jialin Ding, Ryan Marcus, Andreas Kipf, Vikram Nathan, Aniruddha Nrusimha, Kapil Vaidya, Alexander van Renen, Tim Kraska
2021	J	`jnl`	Bounding the Last Mile: Efficient Learned String Indexing. CoRR Benjamin Spector, Andreas Kipf, Kapil Vaidya, Chi Wang, Umar Farooq Minhas, Tim Kraska
2021	J	`jnl`	Defeating duplicates: A re-design of the LearnedSort algorithm. CoRR Ani Kristo, Kapil Vaidya, Tim Kraska
2021	J	`jnl`	Leveraging Query Logs and Machine Learning for Parametric Query Optimization. Proc. VLDB Endow. Kapil Vaidya, Anshuman Dutt, Vivek R. Narasayya, Surajit Chaudhuri
2021	A*	`conf`	Partitioned Learned Bloom Filters. ICLR Kapil Vaidya, Eric Knorr, Michael Mitzenmacher, Tim Kraska
2021	J	`jnl`	When Are Learned Models Better Than Hash Functions? CoRR Ibrahim Sabek, Kapil Vaidya, Dominik Horn, Andreas Kipf, Tim Kraska
2020	J	`jnl`	Partitioned Learned Bloom Filter. CoRR Kapil Vaidya, Eric Knorr, Tim Kraska, Michael Mitzenmacher
2020	—	`conf`	The Case for a Learned Sorting Algorithm. SIGMOD Conference Ani Kristo, Kapil Vaidya, Ugur Çetintemel, Sanchit Misra, Tim Kraska
2018	J	`jnl`	Data-centric dynamic partial order reduction. Proc. ACM Program. Lang. Marek Chalupa, Krishnendu Chatterjee, Andreas Pavlogiannis, Nishant Sinha, Kapil Vaidya
2016	J	`jnl`	Data-centric Dynamic Partial Order Reduction. CoRR Krishnendu Chatterjee, Andreas Pavlogiannis, Nishant Sinha, Kapil Vaidya