no code implementations • 9 Apr 2024 • Zi Long, Zhenhao Tang, Xianghua Fu, Jian Chen, Shilong Hou, Jinze Lyu
Recent research in the field of multimodal machine translation (MMT) has indicated that the visual modality is either dispensable or offers only marginal advantages.
no code implementations • WAT 2022 • Zhenhao Tang, Xiaobing Zhang, Zi Long, Xianghua Fu
However, most of these conclusions are drawn from the analysis of experimental results based on a limited set of bilingual sentence-image pairs, such as Multi30K.
no code implementations • 4 Jul 2019 • Zi Long, Lianzhi Tan, Shengping Zhou, Chaoyang He, Xin Liu
Indicators of Compromise (IOCs) are artifacts observed on a network or in an operating system that can be utilized to indicate a computer intrusion and detect cyber-attacks in an early stage.
no code implementations • PACLIC 2018 • Shengping Zhou, Zi Long, Lianzhi Tan, Hao Guo
In this paper, we propose using a neural-based sequence labelling model to identify IOCs automatically from reports on cybersecurity without expert knowledge of cybersecurity.
no code implementations • WS 2017 • Zi Long, Ryuichiro Kimura, Takehito Utsuro, Tomoharu Mitsuhashi, Mikio Yamamoto
Long et al.(2017) proposed to select phrases that contain out-of-vocabulary words using the statistical approach of branching entropy.
no code implementations • MTSummit 2017 • Zi Long, Ryuichiro Kimura, Takehito Utsuro, Tomoharu Mitsuhashi, Mikio Yamamoto
Neural machine translation (NMT), a new approach to machine translation, has achieved promising results comparable to those of traditional approaches such as statistical machine translation (SMT).
no code implementations • WS 2016 • Zi Long, Takehito Utsuro, Tomoharu Mitsuhashi, Mikio Yamamoto
We train an NMT system on bilingual data wherein technical terms are replaced with technical term tokens; this allows it to translate most of the source sentences except technical terms.