1 code implementation • Findings (EMNLP) 2021 • Yang Zhong, Jingfeng Yang, Wei Xu, Diyi Yang
Biases continue to be prevalent in modern text and media, especially subjective bias – a special type of bias that introduces improper attitudes or presents a statement with the presupposition of truth.
1 code implementation • 27 Mar 2024 • Yang Zhong, Mohamed Elaraby, Diane Litman, Ahmed Ashraf Butt, Muhsin Menekse
This paper introduces ReflectSumm, a novel summarization dataset specifically designed for summarizing students' reflective writing.
1 code implementation • 14 Feb 2024 • Yang Zhong, Hongyu Yu, Jihui Yang, Xingyu Guo, Hongjun Xiang, Xingao Gong
By offering a reliable efficient framework for computing electronic properties, this universal Hamiltonian model lays the groundwork for advancements in diverse fields, such as easily providing a huge data set of electronic structures and also making the materials design across the whole periodic table possible.
no code implementations • 16 Dec 2023 • Yang Zhong, Weiping Dou, Andrew Cohen, Dia'a Bisharat, Yuandong Tian, Jiang Zhu, Qing Huo Liu
To extend the antenna design on printed circuit boards (PCBs) for more engineers of interest, we propose a simple method that models PCB antennas with a few basic components.
1 code implementation • 15 Oct 2023 • Zhexiong Liu, Mohamed Elaraby, Yang Zhong, Diane Litman
This paper presents an overview of the ImageArg shared task, the first multimodal Argument Mining shared task co-located with the 10th Workshop on Argument Mining at EMNLP 2023.
1 code implementation • 29 Sep 2023 • Yang Zhong, Diane Litman
We propose an approach for the structure controllable summarization of long legal opinions that considers the argument structure of the document.
1 code implementation • 1 Jun 2023 • Mohamed Elaraby, Yang Zhong, Diane Litman
We propose a simple approach for the abstractive summarization of long legal opinions that considers the argument structure of the document.
1 code implementation • 21 Nov 2022 • Hongyu Yu, Boyu Liu, Yang Zhong, Liangliang Hong, Junyi Ji, Changsong Xu, Xingao Gong, Hongjun Xiang
This study introduces time-reversal E(3)-equivariant neural network and SpinGNN++ framework for constructing a comprehensive interatomic potential for magnetic systems, encompassing spin-orbit coupling and noncollinear magnetic moments.
1 code implementation • 6 Nov 2022 • Yang Zhong, Diane Litman
Though many algorithms can be used to automatically summarize legal case decisions, most fail to incorporate domain knowledge about how important sentences in a legal decision relate to a representation of its document structure.
Extractive Summarization Unsupervised Extractive Summarization
no code implementations • 28 Oct 2022 • Yang Zhong, Hongyu Yu, Mao Su, Xingao Gong, Hongjun Xiang
Using the message-passing mechanism in machine learning (ML) instead of self-consistent iterations to directly build the mapping from structures to electronic Hamiltonian matrices will greatly improve the efficiency of density functional theory (DFT) calculations.
1 code implementation • Findings (ACL) 2022 • Mert İnan, Yang Zhong, Sabit Hassan, Lorna Quandt, Malihe Alikhani
To employ our strategies, we first annotate a subset of the benchmark PHOENIX-14T, a German Sign Language dataset, with different levels of intensification.
1 code implementation • 6 Mar 2022 • Hongyu Yu, Yang Zhong, Liangliang Hong, Changsong Xu, Wei Ren, Xingao Gong, Hongjun Xiang
The development of machine learning interatomic potentials has immensely contributed to the accuracy of simulations of molecules and crystals.
no code implementations • 28 Feb 2022 • Yang Zhong, Peter Renner, Weiping Dou, Geng Ye, Jiang Zhu, Qing Huo Liu
For a dual resonance antenna design with wide bandwidth, our proposed method is in par with Trust Region Framework and much better than the other mature machine learning algorithms including the widely used Genetic Algorithm and Particle Swarm Optimization.
no code implementations • 15 Jan 2022 • Yang Zhong, Hongyu Yu, Xingao Gong, Hongjun Xiang
Message-passing neural networks (MPNN) have shown extremely high efficiency and accuracy in predicting the physical properties of molecules and crystals, and are expected to become the next-generation material simulation tool after the density functional theory (DFT).
1 code implementation • ACL 2020 • Chao Jiang, Mounica Maddela, Wuwei Lan, Yang Zhong, Wei Xu
The success of a text simplification system heavily depends on the quality and quantity of complex-simple sentence pairs in the training corpus, which are extracted by aligning sentences between parallel articles.
Ranked #1 on Text Simplification on Newsela
no code implementations • 23 Nov 2019 • Yang Zhong, Chao Jiang, Wei Xu, Junyi Jessy Li
We inspect various document and discourse factors associated with sentence deletion, using a new manually annotated sentence alignment corpus we collected.
no code implementations • CVPR 2020 • Yang Zhong, Atsuto Maki
That is, a CNN is efficiently regularized without additional resources of data or prior domain expertise.
no code implementations • 2 Oct 2018 • Yang Zhong, Vladimir Li, Ryuzo Okada, Atsuto Maki
This paper presents an automatic network adaptation method that finds a ConvNet structure well-suited to a given target task, e. g., image classification, for efficiency as well as accuracy in transfer learning.
no code implementations • 12 Feb 2016 • Yang Zhong, Josephine Sullivan, Hai-Bo Li
Predicting attributes from face images in the wild is a challenging computer vision problem.
no code implementations • 4 Feb 2016 • Yang Zhong, Josephine Sullivan, Hai-Bo Li
Predicting facial attributes from faces in the wild is very challenging due to pose and lighting variations in the real world.
no code implementations • 15 Jun 2015 • Yang Zhong, Hai-Bo Li
Different from face verification, face identification is much more demanding.