| Inductive logic programming via differentiable deep neural logic networks A Payani, F Fekri arXiv preprint arXiv:1906.03523, 2019 | 42 | 2019 |
| Large language models can learn temporal reasoning S Xiong, A Payani, R Kompella, F Fekri arXiv preprint arXiv:2401.06853, 2024 | 36 | 2024 |
| Learning algorithms via neural logic networks A Payani, F Fekri arXiv preprint arXiv:1904.01554, 2019 | 32 | 2019 |
| Incorporating relational background knowledge into reinforcement learning via differentiable inductive logic programming A Payani, F Fekri arXiv preprint arXiv:2003.10386, 2020 | 31 | 2020 |
| Advances in seismic data compression via learning from data: Compression for seismic data acquisition A Payani, A Abdi, X Tian, F Fekri, M Mohandes IEEE Signal Processing Magazine 35 (2), 51-61, 2018 | 25 | 2018 |
| Teilp: Time prediction over knowledge graphs via logical reasoning S Xiong, Y Yang, A Payani, JC Kerce, F Fekri Proceedings of the AAAI Conference on Artificial Intelligence 38 (14), 16112 …, 2024 | 19 | 2024 |
| Harnessing the power of large language models for natural language to first-order logic translation Y Yang, S Xiong, A Payani, E Shareghi, F Fekri arXiv preprint arXiv:2305.15541, 2023 | 18 | 2023 |
| Quantifying multilingual performance of large language models across languages Z Li, Y Shi, Z Liu, F Yang, A Payani, N Liu, M Du arXiv preprint arXiv:2404.11553, 2024 | 12 | 2024 |
| Decoding LDPC codes on binary erasure channels using deep recurrent neural-logic layers A Payani, F Fekri 2018 IEEE 10th International Symposium on Turbo Codes & Iterative …, 2018 | 12 | 2018 |
| Learning dictionary for efficient signal compression A Abdi, A Payani, F Fekri 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 12 | 2017 |
| When is tree search useful for llm planning? it depends on the discriminator Z Chen, M White, R Mooney, A Payani, Y Su, H Sun arXiv preprint arXiv:2402.10890, 2024 | 11 | 2024 |
| Text-to-SQL error correction with language models of code Z Chen, S Chen, M White, R Mooney, A Payani, J Srinivasa, Y Su, H Sun arXiv preprint arXiv:2305.13073, 2023 | 9 | 2023 |
| Mitigating group bias in federated learning: Beyond local fairness G Wang, A Payani, M Lee, R Kompella arXiv preprint arXiv:2305.09931, 2023 | 9 | 2023 |
| Eliminating spurious correlations from pre-trained models via data mixing Y Xue, A Payani, Y Yang, B Mirzasoleiman arXiv preprint arXiv:2305.14521, 2023 | 9 | 2023 |
| Compression of seismic signals via recurrent neural networks: Lossy and lossless algorithms A Payani, F Fekri, G Alregib, M Mohandes, M Deriche SEG Technical Program Expanded Abstracts 2019, 4082-4086, 2019 | 9 | 2019 |
| Seismic data compression using online double-sparse dictionary learning schemes E Liu, A Payani, F Fekri 2017 Data Compression Conference (DCC), 449-449, 2017 | 9 | 2017 |
| Data-Efficient Contrastive Language-Image Pretraining: Prioritizing Data Quality over Quantity S Joshi, A Jain, A Payani, B Mirzasoleiman International Conference on Artificial Intelligence and Statistics, 1000-1008, 2024 | 6 | 2024 |
| Eva: An end-to-end exploratory video analytics system GT Kakkar, J Cao, P Chunduri, Z Xu, SR Vyalla, P Dintyala, A Prabakaran, ... Proceedings of the Seventh Workshop on Data Management for End-to-End …, 2023 | 6 | 2023 |
| Prompt mining for language-based human mobility forecasting H Xue, T Tang, A Payani, FD Salim arXiv preprint arXiv:2403.03544, 2024 | 5 | 2024 |
| When fairness meets privacy: Fair classification with semi-private sensitive attributes C Chen, Y Liang, X Xu, S Xie, A Kundu, A Payani, Y Hong, K Shu arXiv preprint arXiv:2207.08336, 2022 | 5 | 2022 |
