1 code implementation • EMNLP 2020 • Zixiang Ding, Rui Xia, Jianfei Yu
To tackle these shortcomings, we propose two joint frameworks for ECPE: 1) multi-label learning for the extraction of the cause clauses corresponding to the specified emotion clause (CMLL) and 2) multi-label learning for the extraction of the emotion clauses corresponding to the specified cause clause (EMLL).
Ranked #3 on Emotion-Cause Pair Extraction on ECPE
1 code implementation • NAACL 2022 • Junjie Li, Jianfei Yu, Rui Xia
As a fundamental task in opinion mining, aspect and opinion co-extraction aims to identify the aspect terms and opinion terms in reviews.
1 code implementation • EMNLP 2021 • Hao Chen, Rui Xia, Jianfei Yu
Data augmentation and adversarial perturbation approaches have recently achieved promising results in solving the over-fitting problem in many natural language processing (NLP) tasks including sentiment classification.
no code implementations • EMNLP 2020 • Rui Xia, Kaizhou Xuan, Jianfei Yu
To address this limitation, we propose a state-independent and time-evolving Network (STN) for rumor detection based on fine-grained event state detection and segmentation.
no code implementations • EMNLP 2020 • Chenggong Gong, Jianfei Yu, Rui Xia
The supervised models for aspect-based sentiment analysis (ABSA) rely heavily on labeled data.
1 code implementation • EMNLP 2021 • Ziheng Liu, Rui Xia, Jianfei Yu
To address these limitations, in this work we first introduce a new Comparative Opinion Quintuple Extraction (COQE) task, to identify comparative sentences from product reviews and extract all comparative opinion quintuples (Subject, Object, Comparative Aspect, Comparative Opinion, Comparative Preference).
no code implementations • EMNLP 2020 • Jianfei Yu, Jing Jiang, Ling Min Serena Khoo, Hai Leong Chieu, Rui Xia
The prevalent use of social media enables rapid spread of rumors on a massive scale, which leads to the emerging need of automatic rumor verification (RV).
1 code implementation • 19 May 2024 • Fanfan Wang, Heqing Ma, Jianfei Yu, Rui Xia, Erik Cambria
The ability to understand emotions is an essential component of human-like artificial intelligence, as emotions greatly influence human cognition, decision making, and social interactions.
1 code implementation • 5 Mar 2024 • Yaochen Zhu, Rui Xia, Jiajun Zhang
In this paper, we introduce a dual-stage method termed Dynamic Pruning Partition Amplification (DPPA), devised to tackle the challenge of merging complex fine-tuned models.
no code implementations • 27 Feb 2024 • Xiangqing Shen, Yurun Song, Siwei Wu, Rui Xia
In this work, we draw inspiration from a commonsense knowledge base ConceptNet in natural language processing, and systematically define the types of visual commonsense.
1 code implementation • 28 Dec 2023 • Zengzhi Wang, Rui Xia, PengFei Liu
Our meticulous data collection and processing efforts included a complex suite of preprocessing, prefiltering, language identification, cleaning, filtering, and deduplication, ensuring the high quality of our corpus.
1 code implementation • 30 Nov 2023 • Yuzhuo Liu, Xubo Liu, Yan Zhao, Yuanyuan Wang, Rui Xia, Pingchuan Tain, Yuxuan Wang
Specifically, APT improves the separation performance of specific sources through training a small number of prompt parameters with limited audio samples, while maintaining the generalization of the USS model by keeping its parameters frozen.
no code implementations • 6 Nov 2023 • Yunlong Chen, Yaming Zhang, Jianfei Yu, Li Yang, Rui Xia
However, generating the most appropriate knowledge base query code based on Natural Language Questions (NLQ) poses a significant challenge in KBQA.
no code implementations • 5 Oct 2023 • Siwei Wu, Xiangqing Shen, Rui Xia
Firstly, EDIT generates open questions related to the dialogue context as the potential user's intention; Then, EDIT answers those questions by interacting with LLMs and searching in domain-specific knowledge bases respectively, and use LLMs to choose the proper answers to questions as extra knowledge; Finally, EDIT enhances response generation by explicitly integrating those extra knowledge.
1 code implementation • 3 Oct 2023 • Qiming Xie, Zengzhi Wang, Yi Feng, Rui Xia
We observe that current conversational language models often waver in their judgements when faced with follow-up questions, even if the original judgement was correct.
1 code implementation • 21 Sep 2023 • Zongqian Zhan, Rui Xia, Yifei Yu, Yibo Xu, Xin Wang
Over the last decades, ample achievements have been made on Structure from motion (SfM).
1 code implementation • 9 Aug 2023 • Xubo Liu, Qiuqiang Kong, Yan Zhao, Haohe Liu, Yi Yuan, Yuzhuo Liu, Rui Xia, Yuxuan Wang, Mark D. Plumbley, Wenwu Wang
In this work, we introduce AudioSep, a foundation model for open-domain audio source separation with natural language queries.
1 code implementation • Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) 2023 • Wenjie Zheng, Jianfei Yu, Rui Xia, Shijin Wang
With the extracted face sequences, we propose a multimodal facial expression-aware emotion recognition model, which leverages the frame-level facial emotion distributions to help improve utterance-level emotion recognition based on multi-task learning.
Ranked #9 on Emotion Recognition in Conversation on MELD
Emotion Recognition in Conversation Facial Expression Recognition (FER)
1 code implementation • 29 Jun 2023 • Hongjie Cai, Nan Song, Zengzhi Wang, Qiming Xie, Qiankun Zhao, Ke Li, Siwei Wu, Shijie Liu, Jianfei Yu, Rui Xia
Aspect-based sentiment analysis is a long-standing research interest in the field of opinion mining, and in recent years, researchers have gradually shifted their focus from simple ABSA subtasks to end-to-end multi-element ABSA tasks.
no code implementations • 14 Jun 2023 • Hengbo Liu, Ziqing Ma, Linxiao Yang, Tian Zhou, Rui Xia, Yi Wang, Qingsong Wen, Liang Sun
In this paper, we propose a novel forecasting framework, named Self-adaptive Decomposed Interpretable framework~(SaDI), which ensembles long-term trend, short-term trend, and period modelings to capture temporal characteristics in different components.
1 code implementation • 26 May 2023 • Siwei Wu, Xiangqing Shen, Rui Xia
To address the two problems, we propose a new CSKG completion framework based on Contrastive Pretraining and Node Clustering (CPNC).
no code implementations • 19 May 2023 • Siyuan Feng, Ming Tu, Rui Xia, Chuanzeng Huang, Yuxuan Wang
Our main approach and adaptation are effective on extremely low-resource languages, even within domain- and language-mismatched scenarios.
no code implementations • 19 May 2023 • Siyuan Feng, Ming Tu, Rui Xia, Chuanzeng Huang, Yuxuan Wang
Moreover, on 3 of the 4 languages, comparing to the standard HuBERT, the approach performs better, meanwhile is able to save supervised training data by 1. 5k hours (75%) at most.
1 code implementation • 10 Apr 2023 • Zengzhi Wang, Qiming Xie, Yi Feng, Zixiang Ding, Zinong Yang, Rui Xia
Recently, ChatGPT has drawn great attention from both the research community and the public.
no code implementations • 5 Apr 2023 • Yaochen Zhu, Xiangqing Shen, Rui Xia
For another, the multimodal reasoning task emphasized the prediction of future states and behaviors but often neglected the incorporation of individual personality traits.
no code implementations • 30 Dec 2022 • Yukun Feng, Ming Tu, Rui Xia, Chuanzeng Huang, Yuxuan Wang
Recent studies have shown that using an external Language Model (LM) benefits the end-to-end Automatic Speech Recognition (ASR).
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 20 Nov 2022 • Zengzhi Wang, Rui Xia, Jianfei Yu
Aspect-Based Sentiment Analysis (ABSA) aims to provide fine-grained aspect-level sentiment information.
Ranked #5 on Aspect-Based Sentiment Analysis (ABSA) on ACOS (using extra training data)
Aspect-Based Sentiment Analysis Aspect-Category-Opinion-Sentiment Quadruple Extraction +5
1 code implementation • 14 Oct 2022 • Xiangqing Shen, Siwei Wu, Rui Xia
Both automatic and human evaluation on an annotated subgraph of ATOMIC demonstrate the advantage of Rel-CSKGC over strong baselines.
1 code implementation • ACL 2022 • Yan Ling, Jianfei Yu, Rui Xia
Further analysis demonstrates the effectiveness of each pretraining task.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1
no code implementations • 14 Apr 2022 • Yun Luo, Hongjie Cai, Linyi Yang, Yanxia Qin, Rui Xia, Yue Zhang
Since previous studies on open-domain targeted sentiment analysis are limited in dataset domain variety and sentence level, we propose a novel dataset consisting of 6, 013 human-labeled data to extend the data domains in topics of interest and document level.
1 code implementation • 14 Mar 2022 • Rui Xia, Chao Xue, Boyu Deng, Fang Wang, JingChao Wang
We study an NLP model called LSRA, which introduces IB with a pyramid-free structure.
no code implementations • 15 Oct 2021 • Fanfan Wang, Zixiang Ding, Rui Xia, Zhaoyu Li, Jianfei Yu
It is also interesting to discover emotions and their causes in conversations.
no code implementations • 7 Oct 2021 • Dongyang Dai, Yuanzhe Chen, Li Chen, Ming Tu, Lu Liu, Rui Xia, Qiao Tian, Yuping Wang, Yuxuan Wang
(2) How to clone a person's voice while controlling the style and prosody.
1 code implementation • ACL 2021 • Hongjie Cai, Rui Xia, Jianfei Yu
In this work, we introduce a new task, named Aspect-Category-Opinion-Sentiment (ACOS) Quadruple Extraction, with the goal to extract all aspect-category-opinion-sentiment quadruples in a review sentence and provide full support for aspect-based sentiment analysis with implicit aspects and opinions.
Aspect-Based Sentiment Analysis Aspect-Category-Opinion-Sentiment Quadruple Extraction +1
no code implementations • COLING 2020 • Hongjie Cai, Yaofeng Tu, Xiangsheng Zhou, Jianfei Yu, Rui Xia
In this work, we re-formalize the task as a category-sentiment hierarchy prediction problem, which contains a hierarchy output structure to first identify multiple aspect categories in a piece of text, and then predict the sentiment for each of the identified categories.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +2
no code implementations • pproximateinference AABI Symposium 2021 • Rui Xia, Wessel Bruinsma, William Tebbutt, Richard E Turner
Many real-world prediction problems involve modelling the dependencies between multiple different outputs across the input space.
3 code implementations • Findings of the Association for Computational Linguistics 2020 • Zhen Wu, Chengcan Ying, Fei Zhao, Zhifang Fan, Xinyu Dai, Rui Xia
To validate the feasibility and compatibility of GTS, we implement three different GTS models respectively based on CNN, BiLSTM, and BERT, and conduct experiments on the aspect-oriented opinion pair extraction and opinion triplet extraction datasets.
Ranked #1 on Aspect Sentiment Triplet Extraction on Res14
Aspect-Sentiment-Opinion Triplet Extraction Aspect Sentiment Triplet Extraction
1 code implementation • ACL 2020 • Jianfei Yu, Jing Jiang, Li Yang, Rui Xia
To tackle the first issue, we propose a multimodal interaction module to obtain both image-aware word representations and word-aware visual representations.
Multi-modal Named Entity Recognition named-entity-recognition +1
1 code implementation • ACL 2020 • Zixiang Ding, Rui Xia, Jianfei Yu
In recent years, a new interesting task, called emotion-cause pair extraction (ECPE), has emerged in the area of text emotion analysis.
Ranked #8 on Emotion-Cause Pair Extraction on ECPE
no code implementations • 26 May 2020 • Dongyang Dai, Li Chen, Yu-Ping Wang, Mu Wang, Rui Xia, Xuchen Song, Zhiyong Wu, Yuxuan Wang
Firstly, the speech synthesis model is pre-trained with both multi-speaker clean data and noisy augmented data; then the pre-trained model is adapted on noisy low-resource new speaker data; finally, by setting the clean speech condition, the model can synthesize the new speaker's clean voice.
4 code implementations • ACL 2019 • Rui Xia, Zixiang Ding
Emotion cause extraction (ECE), the task aimed at extracting the potential causes behind certain emotions in text, has gained much attention in recent years due to its wide applications.
Ranked #13 on Emotion-Cause Pair Extraction on ECPE
1 code implementation • 4 Jun 2019 • Zixiang Ding, Huihui He, Mengran Zhang, Rui Xia
We introduce a relative position augmented embedding learning algorithm, and transform the task from an independent prediction problem to a reordered prediction problem, where the dynamic global label information is incorporated.
Ranked #7 on Emotion Cause Extraction on ECE
3 code implementations • 4 Jun 2019 • Rui Xia, Mengran Zhang, Zixiang Ding
The emotion cause extraction (ECE) task aims at discovering the potential causes behind a certain emotion expression in a document.
Ranked #6 on Emotion Cause Extraction on ECE
no code implementations • 15 Mar 2019 • Rui Xia, Vincent Y. F. Tan, Louis Filstroff, Cédric Févotte
We propose a novel ranking model that combines the Bradley-Terry-Luce probability model with a nonnegative matrix factorization framework to model and uncover the presence of latent variables that influence the performance of top tennis players.
no code implementations • IEEE 2018 • Jianfei Yu, Jing Jiang, Rui Xia
However, most existing methods fail to explicitly consider the syntactic relations among aspect terms and opinion terms, which may lead to the inconsistencies between the model predictions and the syntactic constraints.
Aspect Term Extraction and Sentiment Classification Multi-Task Learning +2
no code implementations • WS 2018 • Saurav Sahay, Shachi H. Kumar, Rui Xia, Jonathan Huang, Lama Nachman
Understanding Affect from video segments has brought researchers from the language, audio and video domains together.
no code implementations • 26 Mar 2018 • Guang-Neng Hu, Xin-yu Dai, Feng-Yu Qiu, Rui Xia, Tao Li, Shu-Jian Huang, Jia-Jun Chen
First, we propose a novel model {\em \mbox{MR3}} to jointly model three sources of information (i. e., ratings, item reviews, and social relations) effectively for rating prediction by aligning the latent factors and hidden topics.
2 code implementations • 3 Feb 2018 • Zixiang Ding, Rui Xia, Jianfei Yu, Xiang Li, Jian Yang
Deep neural networks have recently been shown to achieve highly competitive performance in many computer vision tasks due to their abilities of exploring in a much larger hypothesis space.
1 code implementation • 3 Feb 2018 • Shiliang Zheng, Rui Xia
The target2context attention is used to capture the most indicative sentiment words in left/right contexts.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA)
no code implementations • 3 Feb 2018 • Huihui He, Rui Xia
In this paper, we propose a joint binary neural network (JBNN), to address these shortcomings.
1 code implementation • EMNLP 2017 • Leyi Wang, Rui Xia
Sentiment lexicon is an important tool for identifying the sentiment polarity of words and texts.
no code implementations • 26 Mar 2016 • Qingqing Zhou, Rui Xia, Chengzhi Zhang
Second, international customer behavior study is made easier by integrating tools for multilingual opinion mining.