Search Results - "Nezhurina, Marianna"

MusicLDM: Enhancing Novelty in text-to-music Generation Using Beat-Synchronous mixup Strategies by Chen, Ke, Wu, Yusong, Liu, Haohe, Nezhurina, Marianna, Berg-Kirkpatrick, Taylor, Dubnov, Shlomo

“…Diffusion models have shown promising results in cross-modal generation tasks, including text-to-image and text-to-audio generation. However, generating music,…”
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Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in State-Of-the-Art Large Language Models by Nezhurina, Marianna, Cipolina-Kun, Lucia, Cherti, Mehdi, Jitsev, Jenia

“…Large Language Models (LLMs) are often described as being instances of foundation models - that is, models that transfer strongly across various tasks and…”
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MusicLDM: Enhancing Novelty in Text-to-Music Generation Using Beat-Synchronous Mixup Strategies by Chen, Ke, Wu, Yusong, Liu, Haohe, Nezhurina, Marianna, Berg-Kirkpatrick, Taylor, Dubnov, Shlomo

“…Diffusion models have shown promising results in cross-modal generation tasks, including text-to-image and text-to-audio generation. However, generating music,…”
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Large-scale Contrastive Language-Audio Pretraining with Feature Fusion and Keyword-to-Caption Augmentation by Wu, Yusong, Chen, Ke, Zhang, Tianyu, Hui, Yuchen, Nezhurina, Marianna, Berg-Kirkpatrick, Taylor, Dubnov, Shlomo

“…Contrastive learning has shown remarkable success in the field of multimodal representation learning. In this paper, we propose a pipeline of contrastive…”
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Language models scale reliably with over-training and on downstream tasks by 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…”
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DataComp-LM: In search of the next generation of training sets for language models by 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…”
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BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing by Fries, Jason Alan, Weber, Leon, Seelam, Natasha, Altay, Gabriel, Datta, Debajyoti, Garda, Samuele, Kang, Myungsun, Su, Ruisi, Kusa, Wojciech, Cahyawijaya, Samuel, Barth, Fabio, Ott, Simon, Samwald, Matthias, Bach, Stephen, Biderman, Stella, Sänger, Mario, Wang, Bo, Callahan, Alison, Periñán, Daniel León, Gigant, Théo, Haller, Patrick, Chim, Jenny, Posada, Jose David, Giorgi, John Michael, Sivaraman, Karthik Rangasai, Pàmies, Marc, Nezhurina, Marianna, Martin, Robert, Cullan, Michael, Freidank, Moritz, Dahlberg, Nathan, Mishra, Shubhanshu, Bose, Shamik, Broad, Nicholas Michio, Labrak, Yanis, Deshmukh, Shlok S, Kiblawi, Sid, Singh, Ayush, Vu, Minh Chien, Neeraj, Trishala, Golde, Jonas, del Moral, Albert Villanova, Beilharz, Benjamin

“…Training and evaluating language models increasingly requires the construction of meta-datasets --diverse collections of curated data with clear provenance…”
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