Kexin Rong

41 papers A* 2A 1B 1Journal 27Unranked 7
YearRankTypeTitle / Venue / Authors
2026 J jnl
ActionEngine: From Reactive to Programmatic GUI Agents via State Machine Memory.
CoRR
Hongbin Zhong, Fazle Elahi Faisal, Luis França, Tanakorn Leesatapornwongsa, Adriana Szekeres, Kexin Rong, Suman Nath
2026 J jnl
Halo: Domain-Aware Query Optimization for Long-Context Question Answering.
CoRR
Pramod Chunduri, Francisco Romero, Ali Payani, Kexin Rong, Joy Arulraj
2026 J jnl
VCR: Interpretable and interactive debugging of object detection models with visual concepts.
Inf. Syst.
Jie Jeff Xu, Saahir Dhanani, Jorge Piazentin Ono, Wenbin He, Liu Ren, Kexin Rong
2025 J jnl
A Socratic RAG Approach to Connect Natural Language Queries on Research Topics with Knowledge Organization Systems.
CoRR
Lew Lefton, Kexin Rong, Chinar Dankhara, Lila Ghemri, Firdous Kausar, A. Hannibal Hamdallahi
2025 J jnl
HoneyBee: Efficient Role-based Access Control for Vector Databases via Dynamic Partitioning.
CoRR
Hongbin Zhong, Matthew Lentz, Nina Narodytska, Adriana Szekeres, Kexin Rong
2025 — conf
Ninth Workshop on Human-In-the-Loop Data Analytics (HILDA).
SIGMOD Conference Companion
Remco Chang, Kexin Rong, Roee Shraga
2025 — ed.
Proceedings of the Workshop on Human-In-the-Loop Data Analytics, HILDA 2025, Intercontinental Berlin, Berlin, Germany, June 22-27, 2025
HILDA@SIGMOD
Remco Chang, Kexin Rong, Roee Shraga
2024 B conf
CanDE: A Lightweight Locality-Sensitive Hashing Add-on for Candidate-Based Distribution Estimation.
IEEE Big Data
Jingfan Meng, Huayi Wang, Kexin Rong, Jun Xu
2024 J jnl
Computing in the Era of Large Generative Models: From Cloud-Native to AI-Native.
CoRR
Yao Lu, Song Bian, Lequn Chen, Yongjun He, Yulong Hui, Matthew Lentz, Beibin Li, Fei Liu, Jialin Li, Qi Liu, Rui Liu, Xiaoxuan Liu, Lin Ma, Kexin Rong, Jianguo Wang, Yingjun Wu, Yongji Wu, Huanchen Zhang, Minjia Zhang, Qizhen Zhang, Tianyi Zhou, Danyang Zhuo
2024 J jnl
Demonstration of VCR: A Tabular Data Slicing Approach to Understanding Object Detection Model Performance.
Proc. VLDB Endow.
Jie Jeff Xu, Saahir Dhanani, Jorge Henrique Piazentin Ono, Wenbin He, Liu Ren, Kexin Rong
2024 A* conf
Dynamic Data Layout Optimization with Worst-Case Guarantees.
ICDE
Kexin Rong, Paul Liu, Sarah Ashok Sonje, Moses Charikar
2024 J jnl
Dynamic Data Layout Optimization with Worst-case Guarantees.
CoRR
Kexin Rong, Paul Liu, Sarah Ashok Sonje, Moses Charikar
2024 — conf
Eighth Workshop on Human-In-the-Loop Data Analytics (HILDA).
SIGMOD Conference Companion
Jean-Daniel Fekete, Kexin Rong, Behrooz Omidvar-Tehrani, Roee Shraga
2024 J jnl
Falcon: Fair Active Learning using Multi-armed Bandits.
CoRR
Ki Hyun Tae, Hantian Zhang, Jaeyoung Park, Kexin Rong, Steven Euijong Whang
2024 J jnl
Falcon: Fair Active Learning using Multi-armed Bandits.
Proc. VLDB Endow.
Ki Hyun Tae, Hantian Zhang, Jaeyoung Park, Kexin Rong, Steven Euijong Whang
2024 — conf
Inshrinkerator: Compressing Deep Learning Training Checkpoints via Dynamic Quantization.
SoCC
Amey Agrawal, Sameer Reddy, Satwik Bhattamishra, Venkata Prabhakara Sarath Nookala, Vidushi Vashishth, Kexin Rong, Alexey Tumanov
2024 — conf
Lotus: Characterization of Machine Learning Preprocessing Pipelines via Framework and Hardware Profiling.
IISWC
Rajveer Bachkaniwala, Harshith Lanka, Kexin Rong, Ada Gavrilovska
2024 — ed.
Proceedings of the 2024 Workshop on Human-In-the-Loop Data Analytics, HILDA 24, Santiago, Chile, 14 June 2024
HILDA@SIGMOD
Jean-Daniel Fekete, Behrooz Omidvar-Tehrani, Kexin Rong, Roee Shraga
2024 J jnl
SketchQL Demonstration: Zero-shot Video Moment Querying with Sketches.
CoRR
Renzhi Wu, Pramod Chunduri, Dristi J. Shah, Ashmitha Julius Aravind, Ali Payani, Xu Chu, Joy Arulraj, Kexin Rong
2024 J jnl
SketchQL Demonstration: Zero-shot Video Moment Querying with Sketches.
Proc. VLDB Endow.
Renzhi Wu, Pramod Chunduri, Dristi J. Shah, Ashmitha Julius Aravind, Ali Payani, Xu Chu, Joy Arulraj, Kexin Rong
2024 J jnl
SketchQL: Video Moment Querying with a Visual Query Interface.
Proc. ACM Manag. Data
Renzhi Wu, Pramod Chunduri, Ali Payani, Xu Chu, Joy Arulraj, Kexin Rong
2023 J jnl
DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data.
CoRR
Peng Li, Zhiyi Chen, Xu Chu, Kexin Rong
2023 J jnl
DiffPrep: Differentiable Data Preprocessing Pipeline Search for Learning over Tabular Data.
Proc. ACM Manag. Data
Peng Li, Zhiyi Chen, Xu Chu, Kexin Rong
2023 J jnl
DynaQuant: Compressing Deep Learning Training Checkpoints via Dynamic Quantization.
CoRR
Amey Agrawal, Sameer Reddy, Satwik Bhattamishra, Venkata Prabhakara Sarath Nookala, Vidushi Vashishth, Kexin Rong, Alexey Tumanov
2023 J jnl
Interactive Demonstration of EVA.
Proc. VLDB Endow.
Gaurav Tarlok Kakkar, Aryan Rajoria, Myna Prasanna Kalluraya, Ashmita Raju, Jiashen Cao, Kexin Rong, Joy Arulraj
2023 J jnl
Rethinking Similarity Search: Embracing Smarter Mechanisms over Smarter Data.
CoRR
Renzhi Wu, Jingfan Meng, Jie Jeff Xu, Huayi Wang, Kexin Rong
2023 J jnl
Scaling a Declarative Cluster Manager Architecture with Query Optimization Techniques.
Proc. VLDB Endow.
Kexin Rong, Mihai Budiu, Athinagoras Skiadopoulos, Lalith Suresh, Amy Tai
2021 — —
Improving computational and human efficiency in large-scale data analytics.
Kexin Rong
2020 J jnl
Approximate Partition Selection for Big-Data Workloads using Summary Statistics.
CoRR
Kexin Rong, Yao Lu, Peter Bailis, Srikanth Kandula, Philip Alexander Levis
2020 J jnl
Approximate Partition Selection for Big-Data Workloads using Summary Statistics.
Proc. VLDB Endow.
Kexin Rong, Yao Lu, Peter Bailis, Srikanth Kandula, Philip Alexander Levis
2019 — conf
CrossTrainer: Practical Domain Adaptation with Loss Reweighting.
DEEM@SIGMOD
Justin Chen, Edward Gan, Kexin Rong, Sahaana Suri, Peter Bailis
2019 J jnl
CrossTrainer: Practical Domain Adaptation with Loss Reweighting.
CoRR
Justin Chen, Edward Gan, Kexin Rong, Sahaana Suri, Peter Bailis
2019 A* conf
Rehashing Kernel Evaluation in High Dimensions.
ICML
Paris Siminelakis, Kexin Rong, Peter Bailis, Moses Charikar, Philip Alexander Levis
2018 J jnl
Locality-Sensitive Hashing for Earthquake Detection: A Case Study Scaling Data-Driven Science.
CoRR
Kexin Rong, Clara E. Yoon, Karianne J. Bergen, Hashem Elezabi, Peter Bailis, Philip Alexander Levis, Gregory C. Beroza
2018 J jnl
Locality-Sensitive Hashing for Earthquake Detection: A Case Study Scaling Data-Driven Science.
Proc. VLDB Endow.
Kexin Rong, Clara E. Yoon, Karianne J. Bergen, Hashem Elezabi, Peter Bailis, Philip Alexander Levis, Gregory C. Beroza
2018 J jnl
MacroBase: Prioritizing Attention in Fast Data.
ACM Trans. Database Syst.
Firas Abuzaid, Peter Bailis, Jialin Ding, Edward Gan, Samuel Madden, Deepak Narayanan, Kexin Rong, Sahaana Suri
2017 J jnl
ASAP: Automatic Smoothing for Attention Prioritization in Streaming Time Series Visualization.
CoRR
Kexin Rong, Peter Bailis
2017 J jnl
ASAP: Prioritizing Attention via Time Series Smoothing.
Proc. VLDB Endow.
Kexin Rong, Peter Bailis
2017 — conf
Demonstration: MacroBase, A Fast Data Analysis Engine.
SIGMOD Conference
Peter Bailis, Edward Gan, Kexin Rong, Sahaana Suri
2017 — conf
MacroBase: Prioritizing Attention in Fast Data.
SIGMOD Conference
Peter Bailis, Edward Gan, Samuel Madden, Deepak Narayanan, Kexin Rong, Sahaana Suri
2017 A conf
Prioritizing Attention in Analytic Monitoring.
CIDR
Peter Bailis, Edward Gan, Kexin Rong, Sahaana Suri