Zobrazeno 1 - 10
of 231
pro vyhledávání: '"LI, JEFFREY"'
In this paper, we present SDS (``See it. Do it. Sorted.''), a novel pipeline for intuitive quadrupedal skill learning from a single demonstration video. Leveraging the Visual capabilities of GPT-4o, SDS processes input videos through our novel chain-
Externí odkaz:
http://arxiv.org/abs/2410.11571
Autor:
Nguyen, Thao, Li, Jeffrey, Oh, Sewoong, Schmidt, Ludwig, Weston, Jason, Zettlemoyer, Luke, Li, Xian
We propose a new method, instruction back-and-forth translation, to construct high-quality synthetic data grounded in world knowledge for aligning large language models (LLMs). Given documents from a web corpus, we generate and curate synthetic instr
Externí odkaz:
http://arxiv.org/abs/2408.04614
Autor:
Li, Jeffrey, Fang, Alex, Smyrnis, Georgios, Ivgi, Maor, Jordan, Matt, Gadre, Samir, Bansal, Hritik, Guha, Etash, Keh, Sedrick, Arora, Kushal, Garg, Saurabh, Xin, Rui, Muennighoff, Niklas, Heckel, Reinhard, Mercat, Jean, Chen, Mayee, Gururangan, Suchin, Wortsman, Mitchell, Albalak, Alon, Bitton, Yonatan, Nezhurina, Marianna, Abbas, Amro, Hsieh, Cheng-Yu, Ghosh, Dhruba, Gardner, Josh, Kilian, Maciej, Zhang, Hanlin, Shao, Rulin, Pratt, Sarah, Sanyal, Sunny, Ilharco, Gabriel, Daras, Giannis, Marathe, Kalyani, Gokaslan, Aaron, Zhang, Jieyu, Chandu, Khyathi, Nguyen, Thao, Vasiljevic, Igor, Kakade, Sham, Song, Shuran, Sanghavi, Sujay, Faghri, Fartash, Oh, Sewoong, Zettlemoyer, Luke, Lo, Kyle, El-Nouby, Alaaeldin, Pouransari, Hadi, Toshev, Alexander, Wang, Stephanie, Groeneveld, Dirk, Soldaini, Luca, Koh, Pang Wei, Jitsev, Jenia, Kollar, Thomas, Dimakis, Alexandros G., Carmon, Yair, Dave, Achal, Schmidt, Ludwig, Shankar, Vaishaal
We introduce DataComp for Language Models (DCLM), a testbed for controlled dataset experiments with the goal of improving language models. As part of DCLM, we provide a standardized corpus of 240T tokens extracted from Common Crawl, effective pretrai
Externí odkaz:
http://arxiv.org/abs/2406.11794
Autor:
Gadre, Samir Yitzhak, Smyrnis, Georgios, Shankar, Vaishaal, Gururangan, Suchin, Wortsman, Mitchell, Shao, Rulin, Mercat, Jean, Fang, Alex, Li, Jeffrey, Keh, Sedrick, Xin, Rui, Nezhurina, Marianna, Vasiljevic, Igor, Jitsev, Jenia, Soldaini, Luca, Dimakis, Alexandros G., Ilharco, Gabriel, Koh, Pang Wei, Song, Shuran, Kollar, Thomas, Carmon, Yair, Dave, Achal, Heckel, Reinhard, Muennighoff, Niklas, Schmidt, Ludwig
Scaling laws are useful guides for derisking expensive training runs, as they predict performance of large models using cheaper, small-scale experiments. However, there remain gaps between current scaling studies and how language models are ultimatel
Externí odkaz:
http://arxiv.org/abs/2403.08540
Autor:
Kim, Kyusik Q., Li, Jeffrey J., Nanjaraj Urs, Ankanahalli N., Pacheco, Miguel E., Lasehinde, Victor, Denk, Timo, Tesina, Petr, Tomomatsu, Shota, Matsuo, Yoshitaka, McDonald, Elesa, Beckmann, Roland, Inada, Toshifumi, Green, Rachel, Zaher, Hani S.
Publikováno v:
In Molecular Cell 5 December 2024 84(23):4594-4611
Autor:
Sudarshan, Tarunya Rao, Lim, Sujeung, Li, Jeffrey, Robang, Alicia S., Liberty, Leel Mazal, Ardoña, Herdeline Ann M., Paravastu, Anant K.
Publikováno v:
In Solid State Nuclear Magnetic Resonance October 2024 133
Autor:
Sinha, Niladri K., McKenney, Connor, Yeow, Zhong Y., Li, Jeffrey J., Nam, Ki Hong, Yaron-Barir, Tomer M., Johnson, Jared L., Huntsman, Emily M., Cantley, Lewis C., Ordureau, Alban, Regot, Sergi, Green, Rachel
Publikováno v:
In Cell 11 July 2024 187(14):3652-3670
Despite increasing interest in the field of Interpretable Machine Learning (IML), a significant gap persists between the technical objectives targeted by researchers' methods and the high-level goals of consumers' use cases. In this work, we synthesi
Externí odkaz:
http://arxiv.org/abs/2103.06254
In this paper, we explore connections between interpretable machine learning and learning theory through the lens of local approximation explanations. First, we tackle the traditional problem of performance generalization and bound the test-time accu
Externí odkaz:
http://arxiv.org/abs/2011.01205