Scorch: A Library for Sparse Deep Learning

no code implementations • 27 May 2024 • Bobby Yan, Alexander J. Root, Trevor Gale, David Broman, Fredrik Kjolstad

To bridge this gap, we introduce Scorch, a library that seamlessly integrates efficient sparse tensor computation into the PyTorch ecosystem, with an initial focus on inference workloads on CPUs.

Holistic Evaluation of Language Models

1 code implementation • 16 Nov 2022 • Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel Orr, Lucia Zheng, Mert Yuksekgonul, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda

We present Holistic Evaluation of Language Models (HELM) to improve the transparency of language models.

Fairness Question Answering

FORML: Learning to Reweight Data for Fairness

no code implementations • 3 Feb 2022 • Bobby Yan, Skyler Seto, Nicholas Apostoloff

Machine learning models are trained to minimize the mean loss for a single metric, and thus typically do not consider fairness and robustness.

Fairness Image Classification +2