Robust and Fast 3D Scan Alignment Using Mutual Information. - Nikhil Mehta 002; James R. McBride; Gaurav Pandey 004 (ICRA, 2018)

Deep Topic Models for Multi-label Learning. - Rajat Panda; Ankit Pensia; Nikhil Mehta 002; Mingyuan Zhou; Piyush Rai (AISTATS, 2019)

Stochastic Blockmodels meet Graph Neural Networks. - Nikhil Mehta 002; Lawrence Carin; Piyush Rai (ICML, 2019)

Graph Representation Learning via Ladder Gamma Variational Autoencoders. - Arindam Sarkar; Nikhil Mehta 002; Piyush Rai (AAAI, 2020)

Survival cluster analysis. - Paidamoyo Chapfuwa; Chunyuan Li; Nikhil Mehta 002; Lawrence Carin; Ricardo Henao (CHIL, 2020)

Bayesian Nonparametric Weight Factorization for Continual Learning. - Nikhil Mehta 002; Kevin J. Liang; Lawrence Carin (CoRR, 2020)

Counterfactual Representation Learning with Balancing Weights. - Serge Assaad; Shuxi Zeng; Chenyang Tao; Shounak Datta; Nikhil Mehta 002; Ricardo Henao; Fan Li; Lawrence Carin (AISTATS, 2021)

Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors. - Nikhil Mehta 002; Kevin J. Liang; Vinay Kumar Verma; Lawrence Carin (AISTATS, 2021)

Efficient Feature Transformations for Discriminative and Generative Continual Learning. - Vinay Kumar Verma; Kevin J. Liang; Nikhil Mehta 002; Piyush Rai; Lawrence Carin (CVPR, 2021)

Meta-Learned Attribute Self-Gating for Continual Generalized Zero-Shot Learning. - Vinay Kumar Verma; Kevin J. Liang; Nikhil Mehta 002; Lawrence Carin (CoRR, 2021)

WAFFLe: Weight Anonymized Factorization for Federated Learning. - Weituo Hao; Nikhil Mehta 002; Kevin J. Liang; Pengyu Cheng; Mostafa El-Khamy; Lawrence Carin (IEEE Access, 2022)

Pseudo-OOD training for robust language models. - Dhanasekar Sundararaman; Nikhil Mehta 002; Lawrence Carin (CoRR, 2022)

Towards Efficient Continual Learning in Deep Neural Networks. - Nikhil Mehta 002 (2022)

Recommender Systems with Generative Retrieval. - Shashank Rajput; Nikhil Mehta 002; Anima Singh; Raghunandan Hulikal Keshavan; Trung Vu 002; Lukasz Heldt; Lichan Hong; Yi Tay; Vinh Q. Tran 002; Jonah Samost; Maciej Kula; Ed H. Chi; et al. (NeurIPS, 2023)

Pushing the Efficiency Limit Using Structured Sparse Convolutions. - Vinay Kumar Verma; Nikhil Mehta 002; Shijing Si; Ricardo Henao; Lawrence Carin (WACV, 2023)

Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction. - Wang-Cheng Kang; Jianmo Ni; Nikhil Mehta 002; Maheswaran Sathiamoorthy; Lichan Hong; Ed H. Chi; Derek Zhiyuan Cheng (CoRR, 2023)

Better Generalization with Semantic IDs: A case study in Ranking for Recommendations. - Anima Singh; Trung Vu 002; Raghunandan H. Keshavan; Nikhil Mehta 002; Xinyang Yi; Lichan Hong; Lukasz Heldt; Li Wei; Ed H. Chi; Maheswaran Sathiamoorthy (CoRR, 2023)

Density Weighting for Multi-Interest Personalized Recommendation. - Nikhil Mehta 002; Anima Singh; Xinyang Yi; Sagar Jain; Lichan Hong; Ed H. Chi (CoRR, 2023)

Aligning Large Language Models with Recommendation Knowledge. - Yuwei Cao; Nikhil Mehta 002; Xinyang Yi; Raghunandan Hulikal Keshavan; Lukasz Heldt; Lichan Hong; Ed H. Chi; Maheswaran Sathiamoorthy (NAACL-HLT (Findings), 2024)

Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations. - Anima Singh; Trung Vu 002; Nikhil Mehta 002; Raghunandan H. Keshavan; Maheswaran Sathiamoorthy; Yilin Zheng; Lichan Hong; Lukasz Heldt; Li Wei; Devansh Tandon; Ed H. Chi; Xinyang Yi (RecSys, 2024)

HyperMix: Out-of-Distribution Detection and Classification in Few-Shot Settings. - Nikhil Mehta 002; Kevin J. Liang; Jing Huang 020; Fu-Jen Chu; Li Yin; Tal Hassner (WACV, 2024)

Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning. - Vinay Kumar Verma; Nikhil Mehta 002; Kevin J. Liang; Aakansha Mishra; Lawrence Carin (WACV, 2024)

STAR: A Simple Training-free Approach for Recommendations using Large Language Models. - Dong-Ho Lee; Adam Kraft; Long Jin; Nikhil Mehta 002; Taibai Xu; Lichan Hong; Ed H. Chi; Xinyang Yi (CoRR, 2024)

Building a Mind Palace: Structuring Environment-Grounded Semantic Graphs for Effective Long Video Analysis with LLMs. - Zeyi Huang; Yuyang Ji; Xiaofang Wang; Nikhil Mehta 002; Tong Xiao; Donghyun Lee 004; Sigmund Vanvalkenburgh; Shengxin Zha; Bolin Lai; Licheng Yu; Ning Zhang; Yong Jae Lee; et al. (CVPR, 2025)

Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation. - Bolin Lai; Felix Juefei-Xu; Miao Liu 007; Xiaoliang Dai; Nikhil Mehta 002; Chenguang Zhu; Zeyi Huang; James M. Rehg; Sangmin Lee 001; Ning Zhang; Tong Xiao (CVPR, 2025)

Apollo: An Exploration of Video Understanding in Large Multimodal Models. - Orr Zohar; Xiaohan Wang; Yann Dubois; Nikhil Mehta 002; Tong Xiao; Philippe Hansen-Estruch; Licheng Yu; Xiaofang Wang; Felix Juefei-Xu; Ning Zhang; Serena Yeung-Levy; Xide Xia (CVPR, 2025)

Toward Holistic Evaluation of Recommender Systems Powered by Generative Models. - Yashar Deldjoo; Nikhil Mehta 002; Maheswaran Sathiamoorthy; Shuai Zhang 007; Pablo Castells; Julian J. McAuley (SIGIR, 2025)