1 code implementation • COLING 2022 • Yangjun Wu, Han Wang, Dongxiang Zhang, Gang Chen, Hao Zhang
Specifically, we design 5-type templates as instructional prompts, and each template includes a question that acts as the driver to teach UGEN to grasp the paradigm, options that list the candidate intents or slots to reduce the answer search space, and the context denotes original utterance.
Ranked #1 on
Semantic Frame Parsing
on MixATIS
1 code implementation • 28 Dec 2024 • Yijun Bei, Teng Ma, Dongxiang Zhang, Sai Wu, Kian-Lee Tan, Gang Chen
To address this challenge, we propose a relaxed definition of co-movement patterns from video data, which removes the consecutiveness requirement in the common route and accommodates a certain number of missing captured cameras for objects within the group.
1 code implementation • 30 May 2024 • Zhihao Chang, Linzhu Yu, Huan Li, Sai Wu, Gang Chen, Dongxiang Zhang
To mitigate the computational burden for long trajectories, neural networks have been widely employed for similarity learning and each trajectory is encoded as a high-dimensional vector for similarity search with linear complexity.
1 code implementation • 28 Oct 2023 • Yangjun Wu, Kebin Fang, Dongxiang Zhang, Han Wang, Hao Zhang, Gang Chen
Structured dropout approaches, such as attention dropout and DropHead, have been investigated to regularize the multi-head attention mechanism in Transformers.
no code implementations • 11 Dec 2021 • Renyu Zhu, Dongxiang Zhang, Chengcheng Han, Ming Gao, Xuesong Lu, Weining Qian, Aoying Zhou
More specifically, we construct a bipartite graph for programming problem embedding, and design an improved pre-training model PLCodeBERT for code embedding, as well as a double-sequence RNN model with exponential decay attention for effective feature fusion.
1 code implementation • 2 Sep 2021 • Yihuai Lan, Lei Wang, Qiyuan Zhang, Yunshi Lan, Bing Tian Dai, Yan Wang, Dongxiang Zhang, Ee-Peng Lim
Over the last few years, there are a growing number of datasets and deep learning-based methods proposed for effectively solving MWPs.
Ranked #9 on
Math Word Problem Solving
on Math23K
1 code implementation • Findings (ACL) 2021 • Chengcheng Han, Zeqiu Fan, Dongxiang Zhang, Minghui Qiu, Ming Gao, Aoying Zhou
Meta-learning has emerged as a trending technique to tackle few-shot text classification and achieved state-of-the-art performance.
no code implementations • 17 Dec 2020 • Zhenyu Guo, Mingyu Xiao, Yi Zhou, Dongxiang Zhang, Kian-Lee Tan
The graph edge partition problem, which is to split the edge set into multiple balanced parts to minimize the total number of copied vertices, has been widely studied from the view of optimization and algorithms.
1 code implementation • AAAI 2019 • Lei Wang, Dongxiang Zhang, Jipeng Zhang, Xing Xu, Lianli Gao, Bing Tian Dai, Heng Tao Shen
Then, we design a recursive neural network to encode the quantity with Bi-LSTM and self attention, and infer the unknown operator nodes in a bottom-up manner.
1 code implementation • ACL 2019 • Jierui Li, Lei Wang, Jipeng Zhang, Yan Wang, Bing Tian Dai, Dongxiang Zhang
Several deep learning models have been proposed for solving math word problems (MWPs) automatically.
Ranked #14 on
Math Word Problem Solving
on Math23K
1 code implementation • 1 Jul 2019 • Tao He, Yuan-Fang Li, Lianli Gao, Dongxiang Zhang, Jingkuan Song
We evaluate our framework on {four} public benchmark datasets, all of which show that our method is superior to the other state-of-the-art methods on the tasks of object recognition and image retrieval.
1 code implementation • 14 Nov 2018 • Lei Wang, Yan Wang, Deng Cai, Dongxiang Zhang, Xiaojiang Liu
Moreover, we analyze the performance of three popular SEQ2SEQ models on the math word problem solving.
no code implementations • EMNLP 2018 • Lei Wang, Yan Wang, Deng Cai, Dongxiang Zhang, Xiaojiang Liu
Moreover, we analyze the performance of three popular SEQ2SEQ models on the math word problem solving.
no code implementations • 22 Aug 2018 • Dongxiang Zhang, Lei Wang, Luming Zhang, Bing Tian Dai, Heng Tao Shen
Solving mathematical word problems (MWPs) automatically is challenging, primarily due to the semantic gap between human-readable words and machine-understandable logics.
no code implementations • 22 Aug 2017 • Yazhou Yao, Jian Zhang, Fumin Shen, Li Liu, Fan Zhu, Dongxiang Zhang, Heng-Tao Shen
To eliminate manual annotation, in this work, we propose a novel image dataset construction framework by employing multiple textual queries.
no code implementations • CVPR 2017 • Xing Xu, Fumin Shen, Yang Yang, Dongxiang Zhang, Heng Tao Shen, Jingkuan Song
By additionally introducing manifold regularizations on visual data and semantic embeddings, the learned projection can effectively captures the geometrical manifold structure residing in both visual and semantic spaces.
no code implementations • 5 Jun 2017 • Jingkuan Song, Zhao Guo, Lianli Gao, Wu Liu, Dongxiang Zhang, Heng Tao Shen
Specifically, the proposed framework utilizes the temporal attention for selecting specific frames to predict the related words, while the adjusted temporal attention is for deciding whether to depend on the visual information or the language context information.