no code implementations • Findings (ACL) 2022 • Peixin Huang, Xiang Zhao, Minghao Hu, Yang Fang, Xinyi Li, Weidong Xiao
Secondly, we propose a hybrid selection strategy in the extractor, which not only makes full use of span boundary but also improves the ability of long entity recognition.
no code implementations • COLING 2022 • Biao Hu, Zhen Huang, Minghao Hu, Ziwen Zhang, Yong Dou
Recently, Transformer has achieved great success in Chinese named entity recognition (NER) owing to its good parallelism and ability to model long-range dependencies, which utilizes self-attention to encode context.
Chinese Named Entity Recognition named-entity-recognition +2
1 code implementation • 26 Mar 2024 • Yilin Wang, Minghao Hu, Zhen Huang, Dongsheng Li, Dong Yang, Xicheng Lu
Previous methods for KGC re-ranking are mostly built on non-generative language models to obtain the probability of each candidate.
1 code implementation • 5 Jul 2022 • Qian Huang, Minghao Hu, David Jones Brady
We demonstrate a physics-aware transformer for feature-based data fusion from cameras with diverse resolution, color spaces, focal planes, focal lengths, and exposure.
no code implementations • 17 Jan 2022 • Kaisheng Zeng, Zhenhao Dong, Lei Hou, Yixin Cao, Minghao Hu, Jifan Yu, Xin Lv, Juanzi Li, Ling Feng
Self-supervised entity alignment (EA) aims to link equivalent entities across different knowledge graphs (KGs) without seed alignments.
1 code implementation • 5 Nov 2021 • Chengyu Wang, Minghao Hu, Yuzuru Takashima, Timothy J. Schulz, David J. Brady
We use convolutional neural networks to recover images optically down-sampled by $6. 7\times$ using coherent aperture synthesis over a 16 camera array.
no code implementations • 1 Jul 2020 • Shan Zhao, Minghao Hu, Zhiping Cai, Fang Liu
The network is carefully constructed by stacking multiple attention units in depth to fully model dense interactions over token-label spaces, in which two basic attention units are proposed to explicitly capture fine-grained correlations across different modalities (e. g., token-to-token and labelto-token).
1 code implementation • IJCNLP 2019 • Minghao Hu, Yuxing Peng, Zhen Huang, Dongsheng Li
Rapid progress has been made in the field of reading comprehension and question answering, where several systems have achieved human parity in some simplified settings.
Ranked #8 on Question Answering on DROP Test
1 code implementation • ACL 2019 • Minghao Hu, Yuxing Peng, Zhen Huang, Dongsheng Li
This paper considers the reading comprehension task in which multiple documents are given as input.
1 code implementation • ACL 2019 • Minghao Hu, Yuxing Peng, Zhen Huang, Dongsheng Li, Yiwei Lv
Open-domain targeted sentiment analysis aims to detect opinion targets along with their sentiment polarities from a sentence.
Aspect-Based Sentiment Analysis (ABSA) Aspect Term Extraction and Sentiment Classification +2
no code implementations • EMNLP 2018 • Minghao Hu, Yuxing Peng, Furu Wei, Zhen Huang, Dongsheng Li, Nan Yang, Ming Zhou
Despite that current reading comprehension systems have achieved significant advancements, their promising performances are often obtained at the cost of making an ensemble of numerous models.
no code implementations • 17 Aug 2018 • Minghao Hu, Furu Wei, Yuxing Peng, Zhen Huang, Nan Yang, Dongsheng Li
Machine reading comprehension with unanswerable questions aims to abstain from answering when no answer can be inferred.
Ranked #11 on Question Answering on SQuAD2.0 dev
3 code implementations • 8 May 2017 • Minghao Hu, Yuxing Peng, Zhen Huang, Xipeng Qiu, Furu Wei, Ming Zhou
In this paper, we introduce the Reinforced Mnemonic Reader for machine reading comprehension tasks, which enhances previous attentive readers in two aspects.
Ranked #17 on Question Answering on SQuAD1.1 dev