no code implementations • IEEE Transactions on Image Processing 2014 • Lin Zhang, Ying Shen, Hongyu Li
First, VS is used as a feature when computing the local quality map of the distorted image.
Ranked #7 on Video Quality Assessment on MSU FR VQA Database
3 code implementations • ACL 2018 • Zhun Liu, Ying Shen, Varun Bharadhwaj Lakshminarasimhan, Paul Pu Liang, Amir Zadeh, Louis-Philippe Morency
Previous research in this field has exploited the expressiveness of tensors for multimodal representation.
no code implementations • COLING 2018 • Kai Lei, Daoyuan Chen, Yaliang Li, Nan Du, Min Yang, Wei Fan, Ying Shen
Distantly supervised relation extraction greatly reduces human efforts in extracting relational facts from unstructured texts.
no code implementations • COLING 2018 • Min Yang, Qiang Qu, Ying Shen, Qiao Liu, Wei Zhao, Jia Zhu
Review text has been widely studied in traditional tasks such as sentiment analysis and aspect extraction.
no code implementations • COLING 2018 • Yang Deng, Ying Shen, Min Yang, Yaliang Li, Nan Du, Wei Fan, Kai Lei
In this paper, we propose Knowledge-aware Attentive Network (KAN), a transfer learning framework for cross-domain answer selection, which uses the knowledge base as a bridge to enable knowledge transfer from the source domain to the target domains.
no code implementations • 27 Sep 2018 • Yang Deng, Yaliang Li, Ying Shen, Nan Du, Wei Fan, Min Yang, Kai Lei
In the light of these challenges, we propose a new truth discovery method, MedTruth, for medical knowledge condition discovery, which incorporates prior source quality information into the source reliability estimation procedure, and also utilizes the knowledge triple information for trustworthy information computation.
Databases
4 code implementations • 23 Nov 2018 • Yansen Wang, Ying Shen, Zhun Liu, Paul Pu Liang, Amir Zadeh, Louis-Philippe Morency
Humans convey their intentions through the usage of both verbal and nonverbal behaviors during face-to-face communication.
no code implementations • 5 Dec 2018 • Ying Shen, Joël Colloc, Armelle Jacquet-Andrieu, Ziyi Guo, Yong liu
Disease Ontology (DO) that pertains to cancer's clinical stages and their corresponding information components is utilized to improve the reasoning ability of a decision support system (DSS).
no code implementations • 5 Dec 2018 • Ying Shen, Yang Deng, Kaiqi Yuan, Li Liu, Yong liu
Experiments show that our selected features have achieved a precision rate of 86. 77%, a recall rate of 89. 03% and an F1 score of 87. 89%.
no code implementations • 5 Dec 2018 • Ying Shen, Qiang Zhang, Jin Zhang, Jiyue Huang, Yuming Lu, Kai Lei
However, in electronic medical records (EMR), the texts containing sentences are shorter than that in general domain, which leads to the lack of semantic features and the ambiguity of semantic.
no code implementations • 5 Dec 2018 • Kai Lei, Kaiqi Yuan, Qiang Zhang, Ying Shen
We present MedSim, a novel semantic SIMilarity method based on public well-established bio-MEDical knowledge graphs (KGs) and large-scale corpus, to study the therapeutic substitution of antibiotics.
no code implementations • 5 Dec 2018 • Kai Lei, Bing Zhang, Yong liu, Yang Deng, Dongyu Zhang, Ying Shen
In Question Entity Discovery and Linking (QEDL) problem, traditional methods are challenged because multiple entities in one short question are difficult to be discovered entirely and the incomplete information in short text makes entity linking hard to implement.
2 code implementations • 6 Dec 2018 • Yang Deng, Yuexiang Xie, Yaliang Li, Min Yang, Nan Du, Wei Fan, Kai Lei, Ying Shen
Second, these two tasks can benefit each other: answer selection can incorporate the external knowledge from knowledge base (KB), while KBQA can be improved by learning contextual information from answer selection.
1 code implementation • ACL 2019 • Ziran Li, Ning Ding, Zhiyuan Liu, Hai-Tao Zheng, Ying Shen
Chinese relation extraction is conducted using neural networks with either character-based or word-based inputs, and most existing methods typically suffer from segmentation errors and ambiguity of polysemy.
1 code implementation • 22 Nov 2019 • Yang Deng, Wai Lam, Yuexiang Xie, Daoyuan Chen, Yaliang Li, Min Yang, Ying Shen
Community question answering (CQA) gains increasing popularity in both academy and industry recently.
no code implementations • 21 Jan 2020 • Ying Shen, Jacquet-Andrieu Armelle, Joël Colloc
Our approach is based on the specialization of agents adapted to the knowledge models used during the clinical steps and ontologies.
no code implementations • ACL 2020 • Daoyuan Chen, Yaliang Li, Kai Lei, Ying Shen
Distant supervision based methods for entity and relation extraction have received increasing popularity due to the fact that these methods require light human annotation efforts.
no code implementations • 17 Nov 2020 • Yinghui Li, Ruiyang Liu, Zihao Zhang, Ning Ding, Ying Shen, Linmi Tao, Hai-Tao Zheng
We also provide a theoretical explanation of our method.
Facial Expression Recognition Facial Expression Recognition (FER) +2
no code implementations • COLING 2020 • Dong Wang, Ziran Li, Haitao Zheng, Ying Shen
Dialogue Act Recognition (DAR) is a challenging problem in Natural Language Understanding, which aims to attach Dialogue Act (DA) labels to each utterance in a conversation.
no code implementations • COLING 2020 • Liuyin Wang, Zihan Xu, Zibo Lin, Haitao Zheng, Ying Shen
First, we propose an answer-aware initialization module with a gated connection layer which introduces both document and answer information to the decoder, thus helping to guide the choice of answer-focused question words.
no code implementations • COLING 2020 • Dongming Sheng, Dong Wang, Ying Shen, Haitao Zheng, Haozhuang Liu
Local dependencies, which captures short-term emotional effects between neighbouring utterances, are further injected via an Aggregation Graph to distinguish the subtle differences between utterances containing emotional phrases.
Ranked #29 on Emotion Recognition in Conversation on IEMOCAP
no code implementations • 20 Jan 2021 • Lingyun Feng, Minghui Qiu, Yaliang Li, Hai-Tao Zheng, Ying Shen
Despite pre-trained language models such as BERT have achieved appealing performance in a wide range of natural language processing tasks, they are computationally expensive to be deployed in real-time applications.
no code implementations • 22 Feb 2021 • Yinghui Li, Chen Wang, Yangning Li, Hai-Tao Zheng, Ying Shen
Learning an empirically effective model with generalization using limited data is a challenging task for deep neural networks.
1 code implementation • ICLR 2021 • Ning Ding, Xiaobin Wang, Yao Fu, Guangwei Xu, Rui Wang, Pengjun Xie, Ying Shen, Fei Huang, Hai-Tao Zheng, Rui Zhang
This approach allows us to learn meaningful, interpretable prototypes for the final classification.
no code implementations • 12 Apr 2021 • Yang Deng, Yuexiang Xie, Yaliang Li, Min Yang, Wai Lam, Ying Shen
Answer selection, which is involved in many natural language processing applications such as dialog systems and question answering (QA), is an important yet challenging task in practice, since conventional methods typically suffer from the issues of ignoring diverse real-world background knowledge.
no code implementations • The Thirty-Fifth AAAI Conference on Artificial Intelligence 2021 • Chunpu Xu, Min Yang, Chengming Li, Ying Shen, Xiang Ao, and Ruifeng Xu
Finally, we integrate the imaginary concepts and relational knowledge to generate human-like story based on the original semantics of images.
Ranked #2 on Visual Storytelling on VIST
1 code implementation • ACL 2021 • Binzong Geng, Fajie Yuan, Qiancheng Xu, Ying Shen, Ruifeng Xu, Min Yang
This ability to learn consecutive tasks without forgetting how to perform previously trained problems is essential for developing an online dialogue system.
1 code implementation • EMNLP 2021 • Chenhe Dong, Yaliang Li, Ying Shen, Minghui Qiu
In this paper, we target to compress PLMs with knowledge distillation, and propose a hierarchical relational knowledge distillation (HRKD) method to capture both hierarchical and domain relational information.
no code implementations • 22 Dec 2021 • Chenhe Dong, Yinghui Li, Haifan Gong, Miaoxin Chen, Junxin Li, Ying Shen, Min Yang
This paper offers a comprehensive review of the research on Natural Language Generation (NLG) over the past two decades, especially in relation to data-to-text generation and text-to-text generation deep learning methods, as well as new applications of NLG technology.
1 code implementation • 15 Feb 2022 • Ying Shen, Huiyu Yang, Lin Lin
Depression is a global mental health problem, the worst case of which can lead to suicide.
1 code implementation • 16 Apr 2022 • Yinghui Li, Yangning Li, Yuxin He, Tianyu Yu, Ying Shen, Hai-Tao Zheng
In addition, we propose the ProbExpan, a novel probabilistic ESE framework utilizing the entity representation obtained by the aforementioned language model to expand entities.
1 code implementation • 17 Jul 2022 • Yinghui Li, Shulin Huang, Xinwei Zhang, Qingyu Zhou, Yangning Li, Ruiyang Liu, Yunbo Cao, Hai-Tao Zheng, Ying Shen
In addition, we propose the GAPA, a novel ESE framework that leverages the aforementioned GenerAted PAtterns to expand target entities.
2 code implementations • 19 Oct 2022 • Shirong Ma, Yinghui Li, Rongyi Sun, Qingyu Zhou, Shulin Huang, Ding Zhang, Li Yangning, Ruiyang Liu, Zhongli Li, Yunbo Cao, Haitao Zheng, Ying Shen
Extensive experiments and detailed analyses not only demonstrate that the training data constructed by our method effectively improves the performance of CGEC models, but also reflect that our benchmark is an excellent resource for further development of the CGEC field.
1 code implementation • 29 Oct 2022 • Shulin Huang, Shirong Ma, Yinghui Li, Yangning Li, Shiyang Lin, Hai-Tao Zheng, Ying Shen
Facing this dilemma, we focus on a novel CTG scenario, i. e., blessing generation which is challenging because high-quality blessing texts require CTG models to comprehensively consider the entanglement between multiple attributes (e. g., objects and occasions).
no code implementations • 8 Nov 2022 • Yangning Li, Yinghui Li, Xi Chen, Hai-Tao Zheng, Ying Shen, Hong-Gee Kim
Open Relation Extraction (OpenRE) aims to discover novel relations from open domains.
1 code implementation • 12 Dec 2022 • Chenhe Dong, Yuexiang Xie, Bolin Ding, Ying Shen, Yaliang Li
In this study, we further broaden the application scope of FL in NLP by proposing an Assign-Then-Contrast (denoted as ATC) framework, which enables clients with heterogeneous NLP tasks to construct an FL course and learn useful knowledge from each other.
1 code implementation • 21 Dec 2022 • Zhiyang Xu, Ying Shen, Lifu Huang
Our results indicate that fine-tuning the model on a diverse set of tasks and instructions leads to a reduced sensitivity to variations in instructions for each task.
1 code implementation • 9 Feb 2023 • Ying Shen, Ismini Lourentzou
The research community has shown increasing interest in designing intelligent embodied agents that can assist humans in accomplishing tasks.
no code implementations • 7 Apr 2023 • Shulin Huang, Shirong Ma, Yangning Li, Yinghui Li, Yong Jiang, Hai-Tao Zheng, Ying Shen
For efficiency, expansion time consumed by GenExpan is independent of entity vocabulary and corpus size, and GenExpan achieves an average 600% speedup compared to strong baselines.
no code implementations • 18 May 2023 • Chenhe Dong, Yuexiang Xie, Yaliang Li, Ying Shen
Despite substantial progress in abstractive text summarization to generate fluent and informative texts, the factual inconsistency in the generated summaries remains an important yet challenging problem to be solved.
2 code implementations • 18 May 2023 • Jingheng Ye, Yinghui Li, Qingyu Zhou, Yangning Li, Shirong Ma, Hai-Tao Zheng, Ying Shen
Evaluating the performance of Grammatical Error Correction (GEC) systems is a challenging task due to its subjectivity.
1 code implementation • 24 May 2023 • Jingyuan Qi, Zhiyang Xu, Ying Shen, Minqian Liu, Di Jin, Qifan Wang, Lifu Huang
Chain-of-Thought (CoT) prompting enables large language models to solve complex reasoning problems by generating intermediate steps.
no code implementations • 3 Jun 2023 • Xiaoyan Zhao, Yang Deng, Min Yang, Lingzhi Wang, Rui Zhang, Hong Cheng, Wai Lam, Ying Shen, Ruifeng Xu
This survey is expected to facilitate researchers' collaborative efforts to tackle the challenges of real-life RE systems.
1 code implementation • 12 Jun 2023 • Ziyang Ma, Mengsha Liu, Guian Fang, Ying Shen
False information can spread quickly on social media, negatively influencing the citizens' behaviors and responses to social events.
1 code implementation • 21 Jun 2023 • Yinghui Li, Yong Jiang, Yangning Li, Xingyu Lu, Pengjun Xie, Ying Shen, Hai-Tao Zheng
Entity Linking (EL) is a fundamental task for Information Extraction and Knowledge Graphs.
no code implementations • 30 Jun 2023 • Yinghui Li, Shirong Ma, Shaoshen Chen, Haojing Huang, Shulin Huang, Yangning Li, Hai-Tao Zheng, Ying Shen
During the training process, ProTEC guides the model to learn text error correction by incorporating these sub-tasks into a progressive paradigm.
1 code implementation • 8 Oct 2023 • Jingyuan Qi, Minqian Liu, Ying Shen, Zhiyang Xu, Lifu Huang
Automatically generating scripts (i. e. sequences of key steps described in text) from video demonstrations and reasoning about the subsequent steps are crucial to the modern AI virtual assistants to guide humans to complete everyday tasks, especially unfamiliar ones.
1 code implementation • 12 Nov 2023 • Chenhe Dong, Yuexiang Xie, Bolin Ding, Ying Shen, Yaliang Li
As the global model itself is not required to be shared and the local training is conducted based on an auxiliary model with fewer parameters than the global model, the proposed approach provides protection for the global model while reducing communication and computation costs in FL.
no code implementations • 15 Nov 2023 • Minqian Liu, Ying Shen, Zhiyang Xu, Yixin Cao, Eunah Cho, Vaibhav Kumar, Reza Ghanadan, Lifu Huang
Natural Language Generation (NLG) typically involves evaluating the generated text in various aspects (e. g., consistency and naturalness) to obtain a comprehensive assessment.
1 code implementation • 19 Nov 2023 • Yinghui Li, Zishan Xu, Shaoshen Chen, Haojing Huang, Yangning Li, Yong Jiang, Zhongli Li, Qingyu Zhou, Hai-Tao Zheng, Ying Shen
To the best of our knowledge, Visual-C$^3$ is the first real-world visual and the largest human-crafted dataset for the Chinese character checking scenario.
no code implementations • 31 Jan 2024 • Qirui Jiao, Daoyuan Chen, Yilun Huang, Yaliang Li, Ying Shen
Despite the impressive capabilities of Multimodal Large Language Models (MLLMs) in integrating text and image modalities, challenges remain in accurately interpreting detailed visual elements.
Ranked #37 on Visual Question Answering on MM-Vet
no code implementations • 8 Feb 2024 • Zhenqing Ling, Daoyuan Chen, Liuyi Yao, Yaliang Li, Ying Shen
The confluence of Federated Learning (FL) and Large Language Models (LLMs) is ushering in a new era in privacy-preserving natural language processing.
no code implementations • 18 Feb 2024 • Peng Xing, Yinghui Li, Shirong Ma, Xinnian Liang, Haojing Huang, Yangning Li, Hai-Tao Zheng, Wenhao Jiang, Ying Shen
Chinese Spelling Correction (CSC) aims to detect and correct spelling errors in given sentences.
no code implementations • 18 Feb 2024 • Zhiyang Xu, Chao Feng, Rulin Shao, Trevor Ashby, Ying Shen, Di Jin, Yu Cheng, Qifan Wang, Lifu Huang
Despite vision-language models' (VLMs) remarkable capabilities as versatile visual assistants, two substantial challenges persist within the existing VLM frameworks: (1) lacking task diversity in pretraining and visual instruction tuning, and (2) annotation error and bias in GPT-4 synthesized instruction tuning data.
no code implementations • 24 Feb 2024 • Ying Shen, Zhiyang Xu, Qifan Wang, Yu Cheng, Wenpeng Yin, Lifu Huang
Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in diverse tasks across different domains, with an increasing focus on improving their zero-shot generalization capabilities for unseen multimodal tasks.
no code implementations • 28 Feb 2024 • Zihao Yi, Jiarui Ouyang, YuWen Liu, Tianhao Liao, Zhe Xu, Ying Shen
This survey provides a comprehensive review of research on multi-turn dialogue systems, with a particular focus on multi-turn dialogue systems based on large language models (LLMs).
no code implementations • 17 Mar 2024 • Mengsha Liu, Daoyuan Chen, Yaliang Li, Guian Fang, Ying Shen
Data visualization serves as a critical means for presenting data and mining its valuable insights.
no code implementations • 3 Apr 2024 • Zhe Xu, Daoyuan Chen, Jiayi Kuang, Zihao Yi, Yaliang Li, Ying Shen
Emotional Support Conversation (ESC) systems are pivotal in providing empathetic interactions, aiding users through negative emotional states by understanding and addressing their unique experiences.
no code implementations • 3 Apr 2024 • Ying Shen, Yizhe Zhang, Shuangfei Zhai, Lifu Huang, Joshua M. Susskind, Jiatao Gu
This paper introduces a domain-general framework for many-to-many image generation, capable of producing interrelated image series from a given set of images, offering a scalable solution that obviates the need for task-specific solutions across different multi-image scenarios.
1 code implementation • EMNLP 2020 • Wanwei He, Min Yang, Rui Yan, Chengming Li, Ying Shen, Ruifeng Xu
Instead of adopting the classic student-teacher learning of forcing the output of a student network to exactly mimic the soft targets produced by the teacher networks, we introduce two discriminators as in generative adversarial network (GAN) to transfer knowledge from two teachers to the student.
Ranked #5 on Task-Oriented Dialogue Systems on KVRET
Generative Adversarial Network Task-Oriented Dialogue Systems
no code implementations • EMNLP 2021 • Lingyun Feng, Minghui Qiu, Yaliang Li, Haitao Zheng, Ying Shen
However, the source and target domains usually have different data distributions, which may lead to negative transfer.