no code implementations • SemEval (NAACL) 2022 • Thomas Yim, Junha Lee, Rishi Verma, Scott Hickmann, Annie Zhu, Camron Sallade, Ian Ng, Ryan Chi, Patrick Liu
In this paper, we detail the methods we used to determine the idiomaticity and plausibility of candidate words or phrases into an instructional text as part of the SemEval Task 7: Identifying Plausible Clarifications of Implicit and Underspecified Phrases in Instructional Texts.
no code implementations • 6 Dec 2023 • Samar Khanna, Patrick Liu, Linqi Zhou, Chenlin Meng, Robin Rombach, Marshall Burke, David Lobell, Stefano Ermon
Our method outperforms previous state-of-the-art methods for satellite image generation and is the first large-scale $\textit{generative}$ foundation model for satellite imagery.
no code implementations • 21 Nov 2022 • Eric Mitchell, Joseph J. Noh, Siyan Li, William S. Armstrong, Ananth Agarwal, Patrick Liu, Chelsea Finn, Christopher D. Manning
While large pre-trained language models are powerful, their predictions often lack logical consistency across test inputs.
no code implementations • 17 Jul 2022 • Yezhen Cong, Samar Khanna, Chenlin Meng, Patrick Liu, Erik Rozi, Yutong He, Marshall Burke, David B. Lobell, Stefano Ermon
Unsupervised pre-training methods for large vision models have shown to enhance performance on downstream supervised tasks.
1 code implementation • 8 Nov 2021 • Christopher Yeh, Chenlin Meng, Sherrie Wang, Anne Driscoll, Erik Rozi, Patrick Liu, Jihyeon Lee, Marshall Burke, David B. Lobell, Stefano Ermon
Our goals for SustainBench are to (1) lower the barriers to entry for the machine learning community to contribute to measuring and achieving the SDGs; (2) provide standard benchmarks for evaluating machine learning models on tasks across a variety of SDGs; and (3) encourage the development of novel machine learning methods where improved model performance facilitates progress towards the SDGs.
no code implementations • SEMEVAL 2021 • Erik Rozi, Niveditha Iyer, Gordon Chi, Enok Choe, Kathy J. Lee, Kevin Liu, Patrick Liu, Zander Lack, Jillian Tang, Ethan A. Chi
This paper presents our system for the single- and multi-word lexical complexity prediction tasks of SemEval Task 1: Lexical Complexity Prediction.
no code implementations • SEMEVAL 2021 • Patrick Liu, Niveditha Iyer, Erik Rozi, Ethan A. Chi
This paper presents our system for the Quantity span identification, Unit of measurement identification and Value modifier classification subtasks of the MeasEval 2021 task.