Kaushik Rangadurai

According to our database, Kaushik Rangadurai authored at least 13 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Generative Reasoning Re-ranker.

Mingfu Liang, Yufei Li, Jay Xu, Kavosh Asadi, Xi Liu, Shuo Gu, Kaushik Rangadurai, Frank Shyu, Shuaiwen Wang, Song Yang, Zhijing Li, Jiang Liu, Mengying Sun, Fei Tian, Xiaohan Wei, Chonglin Sun, Jacob Tao, Shike Mei, Wenlin Chen, Santanu Kolay, Sandeep Pandey, Hamed Firooz, Luke Simon

CoRR, February, 2026

Efficient Retrieval Scaling with Hierarchical Indexing for Large Scale Recommendation.

Dongqi Fu, Kaushik Rangadurai, Haiyu Lu, Yunchen Pu, Siyang Yuan, Minhui Huang, Yiqun Liu, Golnaz Ghasemiesfeh, Xingfeng He, Fangzhou Xu, Andrew Cui, Vidhoon Viswanathan, Lin Yang, Liang Wang, Jiyan Yang, Chonglin Sun

Proceedings of the Proceedings 29th International Conference on Extending Database Technology, 2026

2025

ArchPilot: A Proxy-Guided Multi-Agent Approach for Machine Learning Engineering.

Zhuowen Yuan, Tao Liu, Yang Yang, Yang Wang, Feng Qi, Kaushik Rangadurai, Bo Li, Shuang Yang

CoRR, November, 2025

STARK: Strategic Team of Agents for Refining Kernels.

Juncheng Dong, Yang Yang, Tao Liu, Yang Wang, Feng Qi, Vahid Tarokh, Kaushik Rangadurai, Shuang Yang

CoRR, October, 2025

Enhancing Embedding Representation Stability in Recommendation Systems with Semantic ID.

Carolina Zheng, Minhui Huang, Dmitrii Pedchenko, Kaushik Rangadurai, Siyu Wang, Gaby Nahum, Jie Lei, Yang Yang, Tao Liu, Zutian Luo, Xiaohan Wei, Dinesh Ramasamy, Jiyan Yang, Yiping Han, Lin Yang, Hangjun Xu, Rong Jin, Shuang Yang

CoRR, April, 2025

Beyond Self-Consistency: Loss-Balanced Perturbation-Based Regularization Improves Industrial-Scale Ads Ranking.

Ilqar Ramazanli, Hamid Eghbalzadeh, Xiaoyi Liu, Yang Wang, Jiaxiang Fu, Kaushik Rangadurai, Sem Park, Bo Long, Xue Feng

CoRR, February, 2025

Enhancing Embedding Representation Stability in Recommendation Systems with Semantic ID.

Carolina Zheng, Minhui Huang, Dmitrii Pedchenko, Kaushik Rangadurai, Siyu Wang, Fan Xia, Gaby Nahum, Jie Lei, Yang Yang, Tao Liu, Zutian Luo, Xiaohan Wei, Dinesh Ramasamy, Jiyan Yang, Yiping Han, Lin Yang, Hangjun Xu, Rong Jin, Shuang Yang

Proceedings of the Nineteenth ACM Conference on Recommender Systems, 2025

2024

Beyond Self-Consistency: Loss-Balanced Perturbation-Based Regularization Improves Industrial-Scale Ads Ranking.

Ilqar Ramazanli, Hamid Eghbalzadeh, Xiaoyi Liu, Yang Wang, Kaushik Rangadurai, Sem Park, Bo Long, Xue Feng

Proceedings of the IEEE International Conference on Knowledge Graph, 2024

2023

A Distributed Data-Parallel PyTorch Implementation of the Distributed Shampoo Optimizer for Training Neural Networks At-Scale.

Hao-Jun Michael Shi, Tsung-Hsien Lee, Shintaro Iwasaki, Jose Gallego-Posada, Zhijing Li, Kaushik Rangadurai, Dheevatsa Mudigere, Michael Rabbat

CoRR, 2023

2022

NxtPost: User To Post Recommendations In Facebook Groups.

Kaushik Rangadurai, Yiqun Liu, Siddarth Malreddy, Xiaoyi Liu, Piyush Maheshwari, Vishwanath Sangale, Fedor Borisyuk

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

VisRel: Media Search at Scale.

Fedor Borisyuk, Siddarth Malreddy, Jun Mei, Yiqun Liu, Xiaoyi Liu, Piyush Maheshwari, Anthony Bell, Kaushik Rangadurai

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Que2Search: Fast and Accurate Query and Document Understanding for Search at Facebook.

Yiqun Liu, Kaushik Rangadurai, Yunzhong He, Siddarth Malreddy, Xunlong Gui, Xiaoyi Liu, Fedor Borisyuk

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2017

Dionysius: A Framework for Modeling Hierarchical User Interactions in Recommender Systems.

Jian Wang, Krishnaram Kenthapadi, Kaushik Rangadurai, David Hardtke

CoRR, 2017