1 code implementation • CoNLL (EMNLP) 2021 • Yang Hou, Houquan Zhou, Zhenghua Li, Yu Zhang, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan
In the coarse labeling stage, the joint model outputs a bracketed tree, in which each node corresponds to one of four labels (i. e., phrase, subphrase, word, subword).
no code implementations • Findings (EMNLP) 2021 • Ying Li, Meishan Zhang, Zhenghua Li, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan
Thanks to the strong representation learning capability of deep learning, especially pre-training techniques with language model loss, dependency parsing has achieved great performance boost in the in-domain scenario with abundant labeled training data for target domains.
1 code implementation • 19 Apr 2024 • Tianfu Wang, Qilin Fan, Chao Wang, Long Yang, Leilei Ding, Nicholas Jing Yuan, Hui Xiong
In this paper, we propose a FLexible And Generalizable RL framework for VNE, named FlagVNE.
no code implementations • 20 Jun 2023 • Huiguo He, Tianfu Wang, Huan Yang, Jianlong Fu, Nicholas Jing Yuan, Jian Yin, Hongyang Chao, Qi Zhang
The proposed framework consists of a large language model (LLM), a diffusion-based image generator, and a series of visual rewards by design.
no code implementations • 14 Jun 2023 • Likang Wu, Zhi Li, Hongke Zhao, Zhefeng Wang, Qi Liu, Baoxing Huai, Nicholas Jing Yuan, Enhong Chen
Zero-Shot Learning (ZSL), which aims at automatically recognizing unseen objects, is a promising learning paradigm to understand new real-world knowledge for machines continuously.
1 code implementation • CVPR 2023 • Ludan Ruan, Yiyang Ma, Huan Yang, Huiguo He, Bei Liu, Jianlong Fu, Nicholas Jing Yuan, Qin Jin, Baining Guo
To generate joint audio-video pairs, we propose a novel Multi-Modal Diffusion model (i. e., MM-Diffusion), with two-coupled denoising autoencoders.
1 code implementation • KDD 2022 • Liyi Chen, Zhi Li, Tong Xu, Han Wu, Zhefeng Wang, Nicholas Jing Yuan, Enhong Chen
To deal with that problem, in this paper, we propose a novel Multi-modal Siamese Network for Entity Alignment (MSNEA) to align entities in different MMKGs, in which multi-modal knowledge could be comprehensively leveraged by the exploitation of inter-modal effect.
Ranked #7 on Multi-modal Entity Alignment on UMVM-oea-d-w-v1 (using extra training data)
no code implementations • Findings (NAACL) 2022 • Yingjie Gu, Xiaoye Qu, Zhefeng Wang, Yi Zheng, Baoxing Huai, Nicholas Jing Yuan
Recent years have witnessed the improving performance of Chinese Named Entity Recognition (NER) from proposing new frameworks or incorporating word lexicons.
Chinese Named Entity Recognition named-entity-recognition +3
no code implementations • 11 Feb 2022 • Xiangru Zhu, Zhixu Li, Xiaodan Wang, Xueyao Jiang, Penglei Sun, Xuwu Wang, Yanghua Xiao, Nicholas Jing Yuan
In this survey on MMKGs constructed by texts and images, we first give definitions of MMKGs, followed with the preliminaries on multi-modal tasks and techniques.
1 code implementation • 11 Dec 2021 • Tong Zhu, Xiaoye Qu, Wenliang Chen, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan, Min Zhang
Most previous studies of document-level event extraction mainly focus on building argument chains in an autoregressive way, which achieves a certain success but is inefficient in both training and inference.
Ranked #3 on Document-level Event Extraction on ChFinAnn
1 code implementation • 17 Jun 2021 • Wenkai Zhang, Hongyu Lin, Xianpei Han, Le Sun, Huidan Liu, Zhicheng Wei, Nicholas Jing Yuan
Specifically, during neural network training, we naturally model the noise samples in each batch following a hypergeometric distribution parameterized by the noise-rate.
1 code implementation • Findings (ACL) 2021 • Junyi Li, Tianyi Tang, Wayne Xin Zhao, Zhicheng Wei, Nicholas Jing Yuan, Ji-Rong Wen
This paper studies how to automatically generate a natural language text that describes the facts in knowledge graph (KG).
1 code implementation • ACL 2021 • Chen Gong, Saihao Huang, Houquan Zhou, Zhenghua Li, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan
Several previous works on syntactic parsing propose to annotate shallow word-internal structures for better utilizing character-level information.
no code implementations • 9 May 2021 • Junyi Li, Wayne Xin Zhao, Zhicheng Wei, Nicholas Jing Yuan, Ji-Rong Wen
For global coherence, we design a hierarchical self-attentive architecture with both subgraph- and node-level attention to enhance the correlations between subgraphs.
no code implementations • 7 Jan 2021 • Yingjie Gu, Xiaoye Qu, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan, Xiaolin Gui
Entity linking (EL) for the rapidly growing short text (e. g. search queries and news titles) is critical to industrial applications.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Bin He, Di Zhou, Jinghui Xiao, Xin Jiang, Qun Liu, Nicholas Jing Yuan, Tong Xu
Complex node interactions are common in knowledge graphs (KGs), and these interactions can be considered as contextualized knowledge exists in the topological structure of KGs.
1 code implementation • 4 Oct 2020 • Junyi Li, Siqing Li, Wayne Xin Zhao, Gaole He, Zhicheng Wei, Nicholas Jing Yuan, Ji-Rong Wen
First, based on graph capsules, we adaptively learn aspect capsules for inferring the aspect sequence.
no code implementations • 16 Aug 2020 • Zhu Zhang, Zhou Zhao, Zhijie Lin, Baoxing Huai, Nicholas Jing Yuan
Spatio-temporal video grounding aims to retrieve the spatio-temporal tube of a queried object according to the given sentence.
no code implementations • 6 Aug 2020 • Jinglin Liu, Yi Ren, Zhou Zhao, Chen Zhang, Baoxing Huai, Nicholas Jing Yuan
NAR lipreading is a challenging task that has many difficulties: 1) the discrepancy of sequence lengths between source and target makes it difficult to estimate the length of the output sequence; 2) the conditionally independent behavior of NAR generation lacks the correlation across time which leads to a poor approximation of target distribution; 3) the feature representation ability of encoder can be weak due to lack of effective alignment mechanism; and 4) the removal of AR language model exacerbates the inherent ambiguity problem of lipreading.
no code implementations • EMNLP 2020 • Hongyu Lin, Yaojie Lu, Jialong Tang, Xianpei Han, Le Sun, Zhicheng Wei, Nicholas Jing Yuan
Specifically, we erase name regularity, mention coverage and context diversity respectively from the benchmarks, in order to explore their impact on the generalization ability of models.
no code implementations • 30 Nov 2019 • Bin He, Di Zhou, Jinghui Xiao, Xin Jiang, Qun Liu, Nicholas Jing Yuan, Tong Xu
Complex node interactions are common in knowledge graphs, and these interactions also contain rich knowledge information.