Nikhil Mehta - RankMe

44 papers A* 10A 7Journal 24Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	PLUM: Adapting Pre-trained Language Models for Industrial-scale Generative Recommendations. WWW Ruining He, Lukasz Heldt, Lichan Hong, Raghunandan H. Keshavan, Shifan Mao, Nikhil Mehta, Zhengyang Su, Alicia Tsai, Yueqi Wang, Shao-Chuan Wang, Xinyang Yi, Lexi Baugher, Baykal Cakici, Ed H. Chi, Cristos Goodrow, Ningren Han, He Ma, Rómer Rosales, Abby Van Soest, Devansh Tandon, Su-Lin Wu, Weilong Yang, Yilin Zheng
2025	A*	`conf`	Apollo: An Exploration of Video Understanding in Large Multimodal Models. CVPR Orr Zohar, Xiaohan Wang, Yann Dubois, Nikhil Mehta, Tong Xiao, Philippe Hansen-Estruch, Licheng Yu, Xiaofang Wang, Felix Juefei-Xu, Ning Zhang, Serena Yeung-Levy, Xide Xia
2025	A*	`conf`	Building a Mind Palace: Structuring Environment-Grounded Semantic Graphs for Effective Long Video Analysis with LLMs. CVPR Zeyi Huang, Yuyang Ji, Xiaofang Wang, Nikhil Mehta, Tong Xiao, Donghyun Lee, Sigmund Vanvalkenburgh, Shengxin Zha, Bolin Lai, Licheng Yu, Ning Zhang, Yong Jae Lee, Miao Liu
2025	J	`jnl`	Building a Mind Palace: Structuring Environment-Grounded Semantic Graphs for Effective Long Video Analysis with LLMs. CoRR Zeyi Huang, Yuyang Ji, Xiaofang Wang, Nikhil Mehta, Tong Xiao, Donghyun Lee, Sigmund Vanvalkenburgh, Shengxin Zha, Bolin Lai, Licheng Yu, Ning Zhang, Yong Jae Lee, Miao Liu
2025	J	`jnl`	PLUM: Adapting Pre-trained Language Models for Industrial-scale Generative Recommendations. CoRR Ruining He, Lukasz Heldt, Lichan Hong, Raghunandan H. Keshavan, Shifan Mao, Nikhil Mehta, Zhengyang Su, Alicia Tsai, Yueqi Wang, Shao-Chuan Wang, Xinyang Yi, Lexi Baugher, Baykal Cakici, Ed H. Chi, Cristos Goodrow, Ningren Han, He Ma, Rómer Rosales, Abby Van Soest, Devansh Tandon, Su-Lin Wu, Weilong Yang, Yilin Zheng
2025	A*	`conf`	Toward Holistic Evaluation of Recommender Systems Powered by Generative Models. SIGIR Yashar Deldjoo, Nikhil Mehta, Maheswaran Sathiamoorthy, Shuai Zhang, Pablo Castells, Julian J. McAuley
2025	J	`jnl`	Toward Holistic Evaluation of Recommender Systems Powered by Generative Models. CoRR Yashar Deldjoo, Nikhil Mehta, Maheswaran Sathiamoorthy, Shuai Zhang, Pablo Castells, Julian J. McAuley
2025	A*	`conf`	Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation. CVPR Bolin Lai, Felix Juefei-Xu, Miao Liu, Xiaoliang Dai, Nikhil Mehta, Chenguang Zhu, Zeyi Huang, James M. Rehg, Sangmin Lee, Ning Zhang, Tong Xiao
2024	—	`conf`	Aligning Large Language Models with Recommendation Knowledge. NAACL-HLT (Findings) Yuwei Cao, Nikhil Mehta, Xinyang Yi, Raghunandan Hulikal Keshavan, Lukasz Heldt, Lichan Hong, Ed H. Chi, Maheswaran Sathiamoorthy
2024	J	`jnl`	Aligning Large Language Models with Recommendation Knowledge. CoRR Yuwei Cao, Nikhil Mehta, Xinyang Yi, Raghunandan H. Keshavan, Lukasz Heldt, Lichan Hong, Ed H. Chi, Maheswaran Sathiamoorthy
2024	J	`jnl`	Apollo: An Exploration of Video Understanding in Large Multimodal Models. CoRR Orr Zohar, Xiaohan Wang, Yann Dubois, Nikhil Mehta, Tong Xiao, Philippe Hansen-Estruch, Licheng Yu, Xiaofang Wang, Felix Juefei-Xu, Ning Zhang, Serena Yeung-Levy, Xide Xia
2024	A	`conf`	Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations. RecSys Anima Singh, Trung Vu, Nikhil Mehta, Raghunandan H. Keshavan, Maheswaran Sathiamoorthy, Yilin Zheng, Lichan Hong, Lukasz Heldt, Li Wei, Devansh Tandon, Ed H. Chi, Xinyang Yi
2024	A	`conf`	HyperMix: Out-of-Distribution Detection and Classification in Few-Shot Settings. WACV Nikhil Mehta, Kevin J. Liang, Jing Huang, Fu-Jen Chu, Li Yin, Tal Hassner
2024	A	`conf`	Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning. WACV Vinay Kumar Verma, Nikhil Mehta, Kevin J. Liang, Aakansha Mishra, Lawrence Carin
2024	J	`jnl`	STAR: A Simple Training-free Approach for Recommendations using Large Language Models. CoRR Dong-Ho Lee, Adam Kraft, Long Jin, Nikhil Mehta, Taibai Xu, Lichan Hong, Ed H. Chi, Xinyang Yi
2024	J	`jnl`	Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation. CoRR Bolin Lai, Felix Juefei-Xu, Miao Liu, Xiaoliang Dai, Nikhil Mehta, Chenguang Zhu, Zeyi Huang, James M. Rehg, Sangmin Lee, Ning Zhang, Tong Xiao
2023	J	`jnl`	Better Generalization with Semantic IDs: A case study in Ranking for Recommendations. CoRR Anima Singh, Trung Vu, Raghunandan H. Keshavan, Nikhil Mehta, Xinyang Yi, Lichan Hong, Lukasz Heldt, Li Wei, Ed H. Chi, Maheswaran Sathiamoorthy
2023	J	`jnl`	Density Weighting for Multi-Interest Personalized Recommendation. CoRR Nikhil Mehta, Anima Singh, Xinyang Yi, Sagar Jain, Lichan Hong, Ed H. Chi
2023	J	`jnl`	Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction. CoRR Wang-Cheng Kang, Jianmo Ni, Nikhil Mehta, Maheswaran Sathiamoorthy, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng
2023	J	`jnl`	HyperMix: Out-of-Distribution Detection and Classification in Few-Shot Settings. CoRR Nikhil Mehta, Kevin J. Liang, Jing Huang, Fu-Jen Chu, Li Yin, Tal Hassner
2023	J	`jnl`	Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning. CoRR Vinay Kumar Verma, Nikhil Mehta, Kevin J. Liang, Aakansha Mishra, Lawrence Carin
2023	A	`conf`	Pushing the Efficiency Limit Using Structured Sparse Convolutions. WACV Vinay Kumar Verma, Nikhil Mehta, Shijing Si, Ricardo Henao, Lawrence Carin
2023	A*	`conf`	Recommender Systems with Generative Retrieval. NeurIPS Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan Hulikal Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, Mahesh Sathiamoorthy
2023	J	`jnl`	Recommender Systems with Generative Retrieval. CoRR Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan H. Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, Maheswaran Sathiamoorthy
2022	J	`jnl`	Pseudo-OOD training for robust language models. CoRR Dhanasekar Sundararaman, Nikhil Mehta, Lawrence Carin
2022	J	`jnl`	Pushing the Efficiency Limit Using Structured Sparse Convolutions. CoRR Vinay Kumar Verma, Nikhil Mehta, Shijing Si, Ricardo Henao, Lawrence Carin
2022	—	`—`	Towards Efficient Continual Learning in Deep Neural Networks. Nikhil Mehta
2022	J	`jnl`	WAFFLe: Weight Anonymized Factorization for Federated Learning. IEEE Access Weituo Hao, Nikhil Mehta, Kevin J. Liang, Pengyu Cheng, Mostafa El-Khamy, Lawrence Carin
2021	A	`conf`	Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors. AISTATS Nikhil Mehta, Kevin J. Liang, Vinay Kumar Verma, Lawrence Carin
2021	A	`conf`	Counterfactual Representation Learning with Balancing Weights. AISTATS Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin
2021	A*	`conf`	Efficient Feature Transformations for Discriminative and Generative Continual Learning. CVPR Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin
2021	J	`jnl`	Efficient Feature Transformations for Discriminative and Generative Continual Learning. CoRR Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin
2021	J	`jnl`	Meta-Learned Attribute Self-Gating for Continual Generalized Zero-Shot Learning. CoRR Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Lawrence Carin
2020	J	`jnl`	Bayesian Nonparametric Weight Factorization for Continual Learning. CoRR Nikhil Mehta, Kevin J. Liang, Lawrence Carin
2020	J	`jnl`	Counterfactual Representation Learning with Balancing Weights. CoRR Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin
2020	A*	`conf`	Graph Representation Learning via Ladder Gamma Variational Autoencoders. AAAI Arindam Sarkar, Nikhil Mehta, Piyush Rai
2020	J	`jnl`	Survival Cluster Analysis. CoRR Paidamoyo Chapfuwa, Chunyuan Li, Nikhil Mehta, Lawrence Carin, Ricardo Henao
2020	—	`conf`	Survival cluster analysis. CHIL Paidamoyo Chapfuwa, Chunyuan Li, Nikhil Mehta, Lawrence Carin, Ricardo Henao
2020	J	`jnl`	WAFFLe: Weight Anonymized Factorization for Federated Learning. CoRR Weituo Hao, Nikhil Mehta, Kevin J. Liang, Pengyu Cheng, Mostafa El-Khamy, Lawrence Carin
2019	A	`conf`	Deep Topic Models for Multi-label Learning. AISTATS Rajat Panda, Ankit Pensia, Nikhil Mehta, Mingyuan Zhou, Piyush Rai
2019	A*	`conf`	Stochastic Blockmodels meet Graph Neural Networks. ICML Nikhil Mehta, Lawrence Carin, Piyush Rai
2019	J	`jnl`	Stochastic Blockmodels meet Graph Neural Networks. CoRR Nikhil Mehta, Lawrence Carin, Piyush Rai
2018	A*	`conf`	Robust and Fast 3D Scan Alignment Using Mutual Information. ICRA Nikhil Mehta, James R. McBride, Gaurav Pandey
2017	J	`jnl`	Robust and Fast 3D Scan Alignment using Mutual Information. CoRR Nikhil Mehta, James R. McBride, Gaurav Pandey