| Llama 2: Open foundation and fine-tuned chat models H Touvron, L Martin, K Stone, P Albert, A Almahairi, Y Babaei, ... arXiv preprint arXiv:2307.09288, 2023 | 13422 | 2023 |
| 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 | 3482 | 2024 |
| Linformer: Self-attention with linear complexity S Wang, BZ Li, M Khabsa, H Fang, H Ma arXiv preprint arXiv:2006.04768, 2020 | 1866 | 2020 |
| The number of scholarly documents on the public web M Khabsa, CL Giles PloS one 9 (5), e93949, 2014 | 478 | 2014 |
| The CHEMDNER corpus of chemicals and drugs and its annotation principles M Krallinger, O Rabal, F Leitner, M Vazquez, D Salgado, Z Lu, R Leaman, ... Journal of cheminformatics 7, 1-17, 2015 | 394 | 2015 |
| Clear: Contrastive learning for sentence representation Z Wu, S Wang, J Gu, M Khabsa, F Sun, H Ma arXiv preprint arXiv:2012.15466, 2020 | 389 | 2020 |
| Llama guard: Llm-based input-output safeguard for human-ai conversations H Inan, K Upasani, J Chi, R Rungta, K Iyer, Y Mao, M Tontchev, Q Hu, ... arXiv preprint arXiv:2312.06674, 2023 | 349 | 2023 |
| Entailment as few-shot learner S Wang, H Fang, M Khabsa, H Mao, H Ma arXiv preprint arXiv:2104.14690, 2021 | 216 | 2021 |
| Effective long-context scaling of foundation models W Xiong, J Liu, I Molybog, H Zhang, P Bhargava, R Hou, L Martin, ... arXiv preprint arXiv:2309.16039, 2023 | 199 | 2023 |
| Self-attention with linear complexity S Wang, BZ Li, M Khabsa, H Fang, HL Ma arXiv preprint arXiv:2006.04768 175, 176, 2020 | 195 | 2020 |
| Unipelt: A unified framework for parameter-efficient language model tuning Y Mao, L Mathias, R Hou, A Almahairi, H Ma, J Han, W Yih, M Khabsa arXiv preprint arXiv:2110.07577, 2021 | 187 | 2021 |
| Citeseerx: Ai in a digital library search engine J Wu, KM Williams, HH Chen, M Khabsa, C Caragea, S Tuarob, ... AI Magazine 36 (3), 35-48, 2015 | 160 | 2015 |
| Llama 2: Open foundation and fine-tuned chat models. arXiv 2023 H Touvron, L Martin, K Stone, P Albert, A Almahairi, Y Babaei, ... arXiv preprint arXiv:2307.09288 10, 2023 | 157 | 2023 |
| Progressive prompts: Continual learning for language models A Razdaibiedina, Y Mao, R Hou, M Khabsa, M Lewis, A Almahairi arXiv preprint arXiv:2301.12314, 2023 | 148 | 2023 |
| Rayyan: a systematic reviews web app for exploring and filtering searches for eligible studies for Cochrane Reviews AK Elmagarmid, Z Fedorowicz, H Hammady, IF Ilyas, M Khabsa, ... | 114 | 2014 |
| Learning to identify relevant studies for systematic reviews using random forest and external information M Khabsa, A Elmagarmid, I Ilyas, H Hammady, M Ouzzani Machine Learning 102, 465-482, 2016 | 110 | 2016 |
| Language models as fact checkers? N Lee, BZ Li, S Wang, W Yih, H Ma, M Khabsa arXiv preprint arXiv:2006.04102, 2020 | 92 | 2020 |
| Towards few-shot fact-checking via perplexity N Lee, Y Bang, A Madotto, M Khabsa, P Fung arXiv preprint arXiv:2103.09535, 2021 | 87 | 2021 |
| Mart: Improving llm safety with multi-round automatic red-teaming S Ge, C Zhou, R Hou, M Khabsa, YC Wang, Q Wang, J Han, Y Mao arXiv preprint arXiv:2311.07689, 2023 | 83 | 2023 |
| Building natural language interfaces to web apis Y Su, AH Awadallah, M Khabsa, P Pantel, M Gamon, M Encarnacion Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017 | 80 | 2017 |
C Lee GilesPennsylvania State UniversityZweryfikowany adres z psu.edu