Search Results - "Nayak, Nihal"

Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation by Nayak, Nihal V, Nan, Yiyang, Trost, Avi, Bach, Stephen H

“…We introduce Bonito, an open-source model for conditional task generation that converts unannotated text into task-specific training datasets for instruction…”
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100K or 100 Days: Trade-offs when Pre-Training with Academic Resources by Khandelwal, Apoorv, Yun, Tian, Nayak, Nihal V, Merullo, Jack, Bach, Stephen H, Sun, Chen, Pavlick, Ellie

“…Pre-training is notoriously compute-intensive and academic researchers are notoriously under-resourced. It is, therefore, commonly assumed that academics can't…”
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CEREAL: Few-Sample Clustering Evaluation by Nayak, Nihal V, Elenberg, Ethan R, Rosenbaum, Clemens

“…Evaluating clustering quality with reliable evaluation metrics like normalized mutual information (NMI) requires labeled data that can be expensive to…”
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Learning to Compose Soft Prompts for Compositional Zero-Shot Learning by Nayak, Nihal V, Yu, Peilin, Bach, Stephen H

“…We introduce compositional soft prompting (CSP), a parameter-efficient learning technique to improve the zero-shot compositionality of large-scale pretrained…”
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Zero-Shot Learning with Common Sense Knowledge Graphs by Nayak, Nihal V, Bach, Stephen H

“…Zero-shot learning relies on semantic class representations such as hand-engineered attributes or learned embeddings to predict classes without any labeled…”
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Does CLIP Bind Concepts? Probing Compositionality in Large Image Models by Lewis, Martha, Nayak, Nihal V, Yu, Peilin, Yu, Qinan, Merullo, Jack, Bach, Stephen H, Pavlick, Ellie

“…In Findings of the Association for Computational Linguistics, EACL 2024, pages 1487 - 1500, Malta. Association for Computational Linguistics Large-scale neural…”
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TAGLETS: A System for Automatic Semi-Supervised Learning with Auxiliary Data by Piriyakulkij, Wasu, Menghini, Cristina, Briden, Ross, Nayak, Nihal V, Zhu, Jeffrey, Raisi, Elaheh, Bach, Stephen H

“…Machine learning practitioners often have access to a spectrum of data: labeled data for the target task (which is often limited), unlabeled data, and…”
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PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts by Bach, Stephen H, Sanh, Victor, Yong, Zheng-Xin, Webson, Albert, Raffel, Colin, Nayak, Nihal V, Sharma, Abheesht, Kim, Taewoon, Bari, M Saiful, Fevry, Thibault, Alyafeai, Zaid, Dey, Manan, Santilli, Andrea, Sun, Zhiqing, Ben-David, Srulik, Xu, Canwen, Chhablani, Gunjan, Wang, Han, Fries, Jason Alan, Al-shaibani, Maged S, Sharma, Shanya, Thakker, Urmish, Almubarak, Khalid, Tang, Xiangru, Radev, Dragomir, Jiang, Mike Tian-Jian, Rush, Alexander M

“…PromptSource is a system for creating, sharing, and using natural language prompts. Prompts are functions that map an example from a dataset to a natural…”
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Multitask Prompted Training Enables Zero-Shot Task Generalization by Sanh, Victor, Webson, Albert, Raffel, Colin, Bach, Stephen H, Sutawika, Lintang, Alyafeai, Zaid, Chaffin, Antoine, Stiegler, Arnaud, Scao, Teven Le, Raja, Arun, Dey, Manan, Bari, M Saiful, Xu, Canwen, Thakker, Urmish, Sharma, Shanya Sharma, Szczechla, Eliza, Kim, Taewoon, Chhablani, Gunjan, Nayak, Nihal, Datta, Debajyoti, Chang, Jonathan, Jiang, Mike Tian-Jian, Wang, Han, Manica, Matteo, Shen, Sheng, Yong, Zheng Xin, Pandey, Harshit, Bawden, Rachel, Wang, Thomas, Neeraj, Trishala, Rozen, Jos, Sharma, Abheesht, Santilli, Andrea, Fevry, Thibault, Fries, Jason Alan, Teehan, Ryan, Bers, Tali, Biderman, Stella, Gao, Leo, Wolf, Thomas, Rush, Alexander M

“…Large language models have recently been shown to attain reasonable zero-shot generalization on a diverse set of tasks (Brown et al., 2020). It has been…”
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