| The llama 3 herd of models A Grattafiori, A Dubey, A Jauhri, A Pandey, A Kadian, A Al-Dahle, ... arXiv preprint arXiv:2407.21783, 2024 | 3533 | 2024 |
| Recommender systems with generative retrieval S Rajput, N Mehta, A Singh, R Hulikal Keshavan, T Vu, L Heldt, L Hong, ... Advances in Neural Information Processing Systems 36, 10299-10315, 2023 | 170* | 2023 |
| Do llms understand user preferences? evaluating llms on user rating prediction WC Kang, J Ni, N Mehta, M Sathiamoorthy, L Hong, E Chi, DZ Cheng arXiv preprint arXiv:2305.06474, 2023 | 141 | 2023 |
| Stochastic blockmodels meet graph neural networks N Mehta, L Carin, P Rai International Conference on Machine Learning (ICML), 2019 | 109 | 2019 |
| Efficient feature transformations for discriminative and generative continual learning VK Verma, KJ Liang, N Mehta, P Rai, L Carin Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 88 | 2021 |
| Counterfactual representation learning with balancing weights S Assaad, S Zeng, C Tao, S Datta, N Mehta, R Henao, F Li, L Carin International Conference on Artificial Intelligence and Statistics, 1972-1980, 2021 | 85 | 2021 |
| Survival cluster analysis P Chapfuwa, C Li, N Mehta, L Carin, R Henao ACM Conference on Health, Inference, and Learning (CHIL), 2020 | 56 | 2020 |
| Continual learning using a bayesian nonparametric dictionary of weight factors N Mehta, K Liang, VK Verma, L Carin International Conference on Artificial Intelligence and Statistics, 100-108, 2021 | 44* | 2021 |
| Graph Representation Learning via Ladder Gamma Variational Autoencoders A Sarkar, N Mehta, P Rai Association for the Advancement of Artificial Intelligence (AAAI), 2020 | 32 | 2020 |
| Better generalization with semantic ids: A case study in ranking for recommendations A Singh, T Vu, N Mehta, R Keshavan, M Sathiamoorthy, Y Zheng, L Hong, ... Proceedings of the 18th ACM Conference on Recommender Systems, 1039-1044, 2024 | 18* | 2024 |
| Aligning Large Language Models with Recommendation Knowledge Y Cao, N Mehta, X Yi, R Keshavan, L Heldt, L Hong, EH Chi, ... Findings of the Association for Computational Linguistics: NAACL 2024, 1051–1066, 2024 | 18 | 2024 |
| Waffle: Weight anonymized factorization for federated learning W Hao, N Mehta, KJ Liang, P Cheng, M El-Khamy, L Carin IEEE Access 10, 49207-49218, 2022 | 18 | 2022 |
| Meta-learned attribute self-interaction network for continual and generalized zero-shot learning V Verma, N Mehta, KJ Liang, A Mishra, L Carin Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | 15* | 2024 |
| Apollo: An exploration of video understanding in large multimodal models O Zohar, X Wang, Y Dubois, N Mehta, T Xiao, P Hansen-Estruch, L Yu, ... arXiv preprint arXiv:2412.10360, 2024 | 7 | 2024 |
| Deep topic models for multi-label learning R Panda, A Pensia, N Mehta, M Zhou, P Rai The 22nd International Conference on AISTATS, 2849-2857, 2019 | 7 | 2019 |
| Pushing the efficiency limit using structured sparse convolutions VK Verma, N Mehta, S Si, R Henao, L Carin Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 5 | 2023 |
| System and method for federated learning using weight anonymized factorization M El-Khamy, J Lee, HAO Weituo, L Carin, N Mehta, KJ Liang US Patent App. 17/148,557, 2021 | 3 | 2021 |
| HyperMix: Out-of-Distribution Detection and Classification in Few-Shot Settings N Mehta, KJ Liang, J Huang, FJ Chu, L Yin, T Hassner Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | 2 | 2024 |
| Density weighting for multi-interest personalized recommendation N Mehta, A Singh, X Yi, S Jain, L Hong, EH Chi arXiv preprint arXiv:2308.01563, 2023 | 1 | 2023 |
| Building a Mind Palace: Structuring Environment-Grounded Semantic Graphs for Effective Long Video Analysis with LLMs Z Huang, Y Ji, X Wang, N Mehta, T Xiao, D Lee, S Vanvalkenburgh, S Zha, ... arXiv preprint arXiv:2501.04336, 2025 | | 2025 |
Kevin J LiangFundamental AI Research (FAIR) at Meta確認したメール アドレス: meta.com