| Gemini 2.5: Pushing the frontier with advanced reasoning, multimodality, long context, and next generation agentic capabilities G Comanici, E Bieber, M Schaekermann, I Pasupat, N Sachdeva, I Dhillon, ... arXiv preprint arXiv:2507.06261, 2025 | 1337 | 2025 |
| Shared computational principles for language processing in humans and deep language models A Goldstein, Z Zada, E Buchnik, M Schain, A Price, B Aubrey, SA Nastase, ... Nature neuroscience 25 (3), 369-380, 2022 | 559 | 2022 |
| Scalable learning of non-decomposable objectives E Eban, M Schain, A Mackey, A Gordon, R Rifkin, G Elidan Artificial intelligence and statistics, 832-840, 2017 | 151 | 2017 |
| Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns A Goldstein, A Grinstein-Dabush, M Schain, H Wang, Z Hong, B Aubrey, ... Nature communications 15 (1), 2768, 2024 | 69 | 2024 |
| Thinking ahead: spontaneous prediction in context as a keystone of language in humans and machines A Goldstein, Z Zada, E Buchnik, M Schain, A Price, B Aubrey, SA Nastase, ... BioRxiv, 2020.12. 02.403477, 2020 | 65 | 2020 |
| Adversarial robustness of streaming algorithms through importance sampling V Braverman, A Hassidim, Y Matias, M Schain, S Silwal, S Zhou Advances in Neural Information Processing Systems 34, 3544-3557, 2021 | 58 | 2021 |
| Asynchronous stochastic optimization robust to arbitrary delays A Cohen, A Daniely, Y Drori, T Koren, M Schain Advances in Neural Information Processing Systems 34, 9024-9035, 2021 | 53 | 2021 |
| Robust domain adaptation Y Mansour, M Schain Annals of Mathematics and Artificial Intelligence 71 (4), 365-380, 2014 | 51 | 2014 |
| Correspondence between the layered structure of deep language models and temporal structure of natural language processing in the human brain A Goldstein, E Ham, SA Nastase, Z Zada, A Grinstein-Dabus, B Aubrey, ... BioRxiv, 2022.07. 11.499562, 2022 | 40 | 2022 |
| A unified acoustic-to-speech-to-language embedding space captures the neural basis of natural language processing in everyday conversations A Goldstein, H Wang, L Niekerken, M Schain, Z Zada, B Aubrey, T Sheffer, ... Nature human behaviour, 1-15, 2025 | 37 | 2025 |
| System and method for efficiently processing broadband network traffic MR Schain, J Mandin, L Storfer US Patent 6,944,706, 2005 | 35 | 2005 |
| Future meeting evaluation using implicit device feedback E Yom-Tov, MR Schain, M Tennenholtz US Patent App. 14/510,891, 2016 | 26 | 2016 |
| Learning with maximum-entropy distributions Y Mansour, M Schain Machine Learning 45 (2), 123-145, 2001 | 24 | 2001 |
| Deep speech-to-text models capture the neural basis of spontaneous speech in everyday conversations A Goldstein, H Wang, L Niekerken, Z Zada, B Aubrey, T Sheffer, ... bioRxiv, 2023.06. 26.546557, 2023 | 18 | 2023 |
| Ad exchange–proposal for a new trading agent competition game M Schain, Y Mansour International Workshop on Agent-Mediated Electronic Commerce, 133-145, 2012 | 15 | 2012 |
| Machine Learning Algorithms and Robustness M Schain, M Schain Universitat Tel-Aviv, 2015 | 12 | 2015 |
| Brain embeddings with shared geometry to artificial contextual embeddings, as a code for representing language in the human brain A Goldstein, A Dabush, B Aubrey, M Schain, SA Nastase, Z Zada, E Ham, ... BioRxiv, 2022.03. 01.482586, 2022 | 10 | 2022 |
| Protocol performance using ACK filtering J Mandin, M Schain, E Zaltsman, A Gal, L Storfer US Patent App. 10/304,819, 2004 | 10 | 2004 |
| The temporal structure of language processing in the human brain corresponds to the layered hierarchy of deep language models A Goldstein, E Ham, M Schain, S Nastase, Z Zada, A Dabush, B Aubrey, ... arXiv preprint arXiv:2310.07106, 2023 | 9 | 2023 |
| Thinking ahead: prediction in context as a keystone of language in humans and machines. bioRxiv A Goldstein, Z Zada, E Buchnik, M Schain, A Price, B Aubrey, SA Nastase, ... | 8 | 2021 |
avinatan hassidimVerified email at biu.ac.il
