no code implementations • 20 Mar 2024 • Qihao Zhu, Leah Chong, Maria Yang, Jianxi Luo
In human-centered design, developing a comprehensive and in-depth understanding of user experiences, i. e., empathic understanding, is paramount for designing products that truly meet human needs.
1 code implementation • 5 Feb 2024 • Zhihong Shao, Peiyi Wang, Qihao Zhu, Runxin Xu, Junxiao Song, Mingchuan Zhang, Y. K. Li, Y. Wu, Daya Guo
Mathematical reasoning poses a significant challenge for language models due to its complex and structured nature.
Ranked #11 on Math Word Problem Solving on MATH (using extra training data)
1 code implementation • 25 Jan 2024 • Daya Guo, Qihao Zhu, Dejian Yang, Zhenda Xie, Kai Dong, Wentao Zhang, Guanting Chen, Xiao Bi, Y. Wu, Y. K. Li, Fuli Luo, Yingfei Xiong, Wenfeng Liang
The rapid development of large language models has revolutionized code intelligence in software development.
Ranked #10 on Code Generation on MBPP
1 code implementation • 5 Jan 2024 • DeepSeek-AI, :, Xiao Bi, Deli Chen, Guanting Chen, Shanhuang Chen, Damai Dai, Chengqi Deng, Honghui Ding, Kai Dong, Qiushi Du, Zhe Fu, Huazuo Gao, Kaige Gao, Wenjun Gao, Ruiqi Ge, Kang Guan, Daya Guo, JianZhong Guo, Guangbo Hao, Zhewen Hao, Ying He, Wenjie Hu, Panpan Huang, Erhang Li, Guowei Li, Jiashi Li, Yao Li, Y. K. Li, Wenfeng Liang, Fangyun Lin, A. X. Liu, Bo Liu, Wen Liu, Xiaodong Liu, Xin Liu, Yiyuan Liu, Haoyu Lu, Shanghao Lu, Fuli Luo, Shirong Ma, Xiaotao Nie, Tian Pei, Yishi Piao, Junjie Qiu, Hui Qu, Tongzheng Ren, Zehui Ren, Chong Ruan, Zhangli Sha, Zhihong Shao, Junxiao Song, Xuecheng Su, Jingxiang Sun, Yaofeng Sun, Minghui Tang, Bingxuan Wang, Peiyi Wang, Shiyu Wang, Yaohui Wang, Yongji Wang, Tong Wu, Y. Wu, Xin Xie, Zhenda Xie, Ziwei Xie, Yiliang Xiong, Hanwei Xu, R. X. Xu, Yanhong Xu, Dejian Yang, Yuxiang You, Shuiping Yu, Xingkai Yu, B. Zhang, Haowei Zhang, Lecong Zhang, Liyue Zhang, Mingchuan Zhang, Minghua Zhang, Wentao Zhang, Yichao Zhang, Chenggang Zhao, Yao Zhao, Shangyan Zhou, Shunfeng Zhou, Qihao Zhu, Yuheng Zou
The rapid development of open-source large language models (LLMs) has been truly remarkable.
no code implementations • 19 Mar 2023 • Qihao Zhu, Jianxi Luo
Specifically, we conduct an interdisciplinary investigation of research areas such as data-driven user studies, empathic understanding development, and artificial empathy.
no code implementations • 26 Dec 2022 • Qihao Zhu, Xinyu Zhang, Jianxi Luo
This paper proposes a generative design approach based on the generative pre-trained language model (PLM) to automatically retrieve and map biological analogy and generate BID in the form of natural language.
no code implementations • 7 Nov 2022 • Qihao Zhu, Jianxi Luo
Generating novel and useful concepts is essential during the early design stage to explore a large variety of design opportunities, which usually requires advanced design thinking ability and a wide range of knowledge from designers.
no code implementations • 31 Mar 2022 • Qihao Zhu, Xinyu Zhang, Jianxi Luo
Biological systems in nature have evolved for millions of years to adapt and survive the environment.
no code implementations • 28 Mar 2022 • Qihao Zhu, Jianxi Luo
This paper aims to explore a generative approach for knowledge-based design ideation by applying the latest pre-trained language models in artificial intelligence (AI).
no code implementations • 16 Nov 2021 • Qihao Zhu, Jianxi Luo
Novel concepts are essential for design innovation and can be generated with the aid of data stimuli and computers.
1 code implementation • 27 Aug 2021 • Qingyuan Liang, Zeyu Sun, Qihao Zhu, Wenjie Zhang, Lian Yu, Yingfei Xiong, Lu Zhang
Since a declarative language is typically embedded in an imperative language (i. e., the turducken-style programming) in real-world software development, the promising results on declarative languages can hardly lead to significant reduction of manual software development efforts.
1 code implementation • 15 Jun 2021 • Qihao Zhu, Zeyu Sun, Yuan-an Xiao, Wenjie Zhang, Kang Yuan, Yingfei Xiong, Lu Zhang
Our results show that Recoder repairs 53 bugs on Defects4J v1. 2, which achieves 21. 4% improvement over the previous state-of-the-art approach for single-hunk bugs (TBar).
1 code implementation • 23 Feb 2021 • Zeyu Sun, Wenjie Zhang, Lili Mou, Qihao Zhu, Yingfei Xiong, Lu Zhang
Existing graph neural networks (GNNs) largely rely on node embeddings, which represent a node as a vector by its identity, type, or content.
2 code implementations • 12 Aug 2020 • Qihao Zhu, Zeyu Sun, Xiran Liang, Yingfei Xiong, Lu Zhang
To address these problems, we propose a novel neural architecture named OCoR, where we introduce two specifically-designed components to capture overlaps: the first embeds identifiers by character to capture the overlaps between identifiers, and the second introduces a novel overlap matrix to represent the degrees of overlaps between each natural language word and each identifier.
1 code implementation • 26 Jan 2020 • Wenjie Zhang, Zeyu Sun, Qihao Zhu, Ge Li, Shaowei Cai, Yingfei Xiong, Lu Zhang
However, in this method, the initialization is assigned in a random manner, which impacts the effectiveness of SLS solvers.
2 code implementations • 22 Nov 2019 • Zeyu Sun, Qihao Zhu, Yingfei Xiong, Yican Sun, Lili Mou, Lu Zhang
TreeGen outperformed the previous state-of-the-art approach by 4. 5 percentage points on HearthStone, and achieved the best accuracy among neural network-based approaches on ATIS (89. 1%) and GEO (89. 6%).
1 code implementation • 14 Nov 2018 • Zeyu Sun, Qihao Zhu, Lili Mou, Yingfei Xiong, Ge Li, Lu Zhang
In this paper, we propose a grammar-based structural convolutional neural network (CNN) for code generation.