1 code implementation • 28 Feb 2024 • Zilin Xiao, Ming Gong, Paola Cascante-Bonilla, Xingyao Zhang, Jie Wu, Vicente Ordonez
We introduce AutoVER, an Autoregressive model for Visual Entity Recognition.
1 code implementation • 16 Nov 2023 • Xiangru Tang, Anni Zou, Zhuosheng Zhang, Ziming Li, Yilun Zhao, Xingyao Zhang, Arman Cohan, Mark Gerstein
Large language models (LLMs), despite their remarkable progress across various general domains, encounter significant barriers in medicine and healthcare.
no code implementations • 6 Nov 2023 • Zilin Xiao, Linjun Shou, Xingyao Zhang, Jie Wu, Ming Gong, Jian Pei, Daxin Jiang
We propose CoherentED, an ED system equipped with novel designs aimed at enhancing the coherence of entity predictions.
1 code implementation • 6 Nov 2023 • Zilin Xiao, Ming Gong, Jie Wu, Xingyao Zhang, Linjun Shou, Jian Pei, Daxin Jiang
Generative approaches powered by large language models (LLMs) have demonstrated emergent abilities in tasks that require complex reasoning abilities.
1 code implementation • 27 Apr 2023 • Joo Hyung Lee, Wonpyo Park, Nicole Mitchell, Jonathan Pilault, Johan Obando-Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart Bik, Woohyun Han, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann Dauphin, Gintare Karolina Dziugaite, Pablo Samuel Castro, Utku Evci
This paper introduces JaxPruner, an open-source JAX-based pruning and sparse training library for machine learning research.
no code implementations • 7 Oct 2021 • Qiyu Wan, Haojun Xia, Xingyao Zhang, Lening Wang, Shuaiwen Leon Song, Xin Fu
Bayesian Neural Networks (BNNs) that possess a property of uncertainty estimation have been increasingly adopted in a wide range of safety-critical AI applications which demand reliable and robust decision making, e. g., self-driving, rescue robots, medical image diagnosis.
1 code implementation • 22 Jun 2021 • Donglin Zhuang, Xingyao Zhang, Shuaiwen Leon Song, Sara Hooker
However, we also find that the cost of ensuring determinism varies dramatically between neural network architectures and hardware types, e. g., with overhead up to $746\%$, $241\%$, and $196\%$ on a spectrum of widely used GPU accelerator architectures, relative to non-deterministic training.
no code implementations • COLING 2020 • Xingyao Zhang, Linjun Shou, Jian Pei, Ming Gong, Lijie Wen, Daxin Jiang
The abundant semi-structured data on the Web, such as HTML-based tables and lists, provide commercial search engines a rich information source for question answering (QA).
no code implementations • 22 Jan 2020 • Xingyao Zhang, Cao Xiao, Lucas M. Glass, Jimeng Sun
To address these challenges, we proposed DeepEnroll, a cross-modal inference learning model to jointly encode enrollment criteria (text) and patients records (tabular data) into a shared latent space for matching inference.
no code implementations • 7 Nov 2019 • Xingyao Zhang, Shuaiwen Leon Song, Chenhao Xie, Jing Wang, Weigong Zhang, Xin Fu
In recent years, the CNNs have achieved great successes in the image processing tasks, e. g., image recognition and object detection.