| How to train your hippo: State space models with generalized orthogonal basis projections A Gu, I Johnson, A Timalsina, A Rudra, C Ré arXiv preprint arXiv:2206.12037, 2022 | 42 | 2022 |
| Zoology: Measuring and improving recall in efficient language models S Arora, S Eyuboglu, A Timalsina, I Johnson, M Poli, J Zou, A Rudra, C Ré arXiv preprint arXiv:2312.04927, 2023 | 9 | 2023 |
| Laughing hyena distillery: Extracting compact recurrences from convolutions S Massaroli, M Poli, D Fu, H Kumbong, R Parnichkun, D Romero, ... Advances in Neural Information Processing Systems 36, 2024 | 6* | 2024 |
| Computing Generalized Ranks of Persistence Modules via Unfolding to Zigzag Modules TK Dey, A Timalsina, C Xin arXiv preprint arXiv:2403.08110, 2024 | | 2024 |
| Simple linear attention language models balance the recall-throughput tradeoff S Arora, S Eyuboglu, M Zhang, A Timalsina, S Alberti, D Zinsley, J Zou, ... arXiv preprint arXiv:2402.18668, 2024 | | 2024 |
| On input-dependence and recall in convolutional language models S Arora, S Eyuboglu, A Timalsina, I Johnson, M Poli, J Zou, A Rudra, C Re The Twelfth International Conference on Learning Representations, 2023 | | 2023 |
| Tetrahedralization of a Hexahedral Mesh A Timalsina, MG Knepley International Meshing Roundtable, 2022 | | 2022 |
| Measuring and Improving Recall in Convolutional Language Models S Arora, S Eyuboglu, A Timalsina, I Johnson, M Poli, J Zou, A Rudra, C Ré | | |
