no code implementations • EMNLP 2020 • Yiquan Wu, Kun Kuang, Yating Zhang, Xiaozhong Liu, Changlong Sun, Jun Xiao, Yueting Zhuang, Luo Si, Fei Wu
Court{'}s view generation is a novel but essential task for legal AI, aiming at improving the interpretability of judgment prediction results and enabling automatic legal document generation.
no code implementations • 26 May 2025 • Weikang Yuan, Kaisong Song, Zhuoren Jiang, Junjie Cao, Yujie Zhang, Jun Lin, Kun Kuang, Ji Zhang, Xiaozhong Liu
To address these challenges, we introduce LeCoDe, a real-world multi-turn benchmark dataset comprising 3, 696 legal consultation dialogues with 110, 008 dialogue turns, designed to evaluate and improve LLMs' legal consultation capability.
no code implementations • 24 May 2025 • Yiqing Zhang, Xiaozhong Liu, Fabricio Murai
To address this limitation, we introduce CLaDMoP, a new pre-training approach for clinical trial outcome prediction, alongside the Successful Clinical Trials dataset(SCT), specifically designed for this task.
1 code implementation • 22 May 2025 • YuTing Huang, Meitong Guo, Yiquan Wu, Ang Li, Xiaozhong Liu, Keting Yin, Changlong Sun, Fei Wu, Kun Kuang
Recent advances in LegalAI have primarily focused on individual case judgment analysis, often overlooking the critical appellate process within the judicial system.
no code implementations • 27 Feb 2025 • Kai Zhang, Rui Zhu, Shutian Ma, Jingwei Xiong, Yejin Kim, Fabricio Murai, Xiaozhong Liu
Drug discovery is a critical task in biomedical natural language processing (NLP), yet explainable drug discovery remains underexplored.
1 code implementation • 11 Feb 2025 • Rujing Yao, Yang Wu, Chenghao Wang, Jingwei Xiong, Fang Wang, Xiaozhong Liu
Large Language Models (LLMs) have achieved impressive results across numerous domains, yet they experience notable deficiencies in legal question-answering tasks.
no code implementations • 11 Feb 2025 • Param Kulkarni, Yingchi Liu, Hao-Ming Fu, Shaohua Yang, Isuru Gunasekara, Matt Peloquin, Noah Spitzer-Williams, Xiaotian Zhou, Xiaozhong Liu, Zhengping Ji, Yasser Ibrahim
Achieving a delicate balance between fostering trust in law en- forcement and protecting the rights of both officers and civilians continues to emerge as a pressing research and product challenge in the world today.
no code implementations • 3 Feb 2025 • Yuyang Gong, Zhuo Chen, Miaokun Chen, Fengchang Yu, Wei Lu, XiaoFeng Wang, Xiaozhong Liu, Jiawei Liu
Retrieval-Augmented Generation (RAG) systems based on Large Language Models (LLMs) have become essential for tasks such as question answering and content generation.
1 code implementation • 12 Jan 2025 • Yiqing Zhang, Xiaozhong Liu, Fabricio Murai
Clinical trials are the gold standard for assessing the effectiveness and safety of drugs for treating diseases.
no code implementations • 6 Jan 2025 • Zhuo Chen, Jiawei Liu, Yuyang Gong, Miaokun Chen, Haotan Liu, Qikai Cheng, Fan Zhang, Wei Lu, Xiaozhong Liu, XiaoFeng Wang
In this paper, we investigate a more realistic and critical threat scenario: adversarial attacks intended for opinion manipulation against black-box RAG models, particularly on controversial topics.
no code implementations • 1 Dec 2024 • Yang Wu, Huayi Zhang, Yizheng Jiao, Lin Ma, Xiaozhong Liu, Jinhong Yu, Dongyu Zhang, Dezhi Yu, Wei Xu
In this work, we focus on the data selection problem for task-specific instruction tuning of LLMs.
1 code implementation • 22 Oct 2024 • Haining Wang, Jason Clark, Hannah McKelvey, Leila Sterman, Zheng Gao, Zuoyu Tian, Sandra Kübler, Xiaozhong Liu
A vast amount of scholarly work is published daily, yet much of it remains inaccessible to the general public due to dense jargon and complex language.
no code implementations • 19 Oct 2024 • Tianqianjin Lin, Pengwei Yan, Kaisong Song, Zhuoren Jiang, Yangyang Kang, Jun Lin, Weikang Yuan, Junjie Cao, Changlong Sun, Xiaozhong Liu
Graph foundation models (GFMs) have recently gained significant attention.
no code implementations • 12 Oct 2024 • Kaisong Song, Yangyang Kang, Jiawei Liu, Xurui Li, Changlong Sun, Xiaozhong Liu
It is observed that whether the user's needs are met often triggers various sentiments, which can be pertinent to the successful estimation of user satisfaction, and vice versa.
no code implementations • 10 Oct 2024 • Kai Zhang, Liqian Peng, Congchao Wang, Alec Go, Xiaozhong Liu
Large Language Models (LLMs) have demonstrated exceptional capabilities in understanding and generating natural language.
1 code implementation • 3 Oct 2024 • Weikang Yuan, Junjie Cao, Zhuoren Jiang, Yangyang Kang, Jun Lin, Kaisong Song, Tianqianjin Lin, Pengwei Yan, Changlong Sun, Xiaozhong Liu
Large Language Models (LLMs) could struggle to fully understand legal theories and perform complex legal reasoning tasks.
no code implementations • 15 Sep 2024 • Yuehan Zhang, Peizhuo Lv, Yinpeng Liu, Yongqiang Ma, Wei Lu, XiaoFeng Wang, Xiaozhong Liu, Jiawei Liu
To the best of our knowledge, this is a pioneer study to explore personalized watermarking in LLMs.
no code implementations • 18 Jul 2024 • Zhuo Chen, Jiawei Liu, Haotan Liu, Qikai Cheng, Fan Zhang, Wei Lu, Xiaozhong Liu
Retrieval-Augmented Generation (RAG) is applied to solve hallucination problems and real-time constraints of large language models, but it also induces vulnerabilities against retrieval corruption attacks.
no code implementations • 5 Jun 2024 • Yang Wu, Chenghao Wang, Ece Gumusel, Xiaozhong Liu
The integration of generative Large Language Models (LLMs) into various applications, including the legal domain, has been accelerated by their expansive and versatile nature.
no code implementations • 18 Apr 2024 • Zi Xiong, Lizhi Qing, Yangyang Kang, Jiawei Liu, Hongsong Li, Changlong Sun, Xiaozhong Liu, Wei Lu
The widespread use of pre-trained language models (PLMs) in natural language processing (NLP) has greatly improved performance outcomes.
no code implementations • 10 Apr 2024 • Yongqiang Ma, Lizhi Qing, Jiawei Liu, Yangyang Kang, Yue Zhang, Wei Lu, Xiaozhong Liu, Qikai Cheng
Therefore, our study shifts the focus from model-centered to human-centered evaluation in the context of AI-powered writing assistance applications.
1 code implementation • 4 Apr 2024 • Kai Zhang, Yejin Kim, Xiaozhong Liu
Large Language Models (LLMs) have exhibited remarkable proficiency in comprehending and generating natural language.
1 code implementation • 19 Dec 2023 • Pengwei Yan, Kaisong Song, Zhuoren Jiang, Yangyang Kang, Tianqianjin Lin, Changlong Sun, Xiaozhong Liu
While self-supervised graph pretraining techniques have shown promising results in various domains, their application still experiences challenges of limited topology learning, human knowledge dependency, and incompetent multi-level interactions.
no code implementations • 10 Dec 2023 • Tianqianjin Lin, Kaisong Song, Zhuoren Jiang, Yangyang Kang, Weikang Yuan, Xurui Li, Changlong Sun, Cui Huang, Xiaozhong Liu
Heterogeneous graph neural networks have become popular in various domains.
no code implementations • 13 Oct 2023 • Yiquan Wu, Siying Zhou, Yifei Liu, Weiming Lu, Xiaozhong Liu, Yating Zhang, Changlong Sun, Fei Wu, Kun Kuang
Precedents are the previous legal cases with similar facts, which are the basis for the judgment of the subsequent case in national legal systems.
no code implementations • 28 Sep 2023 • Xiaotian Zhou, Qian Wang, XiaoFeng Wang, Haixu Tang, Xiaozhong Liu
Large language models (LLMs) have demonstrated human-level performance on a vast spectrum of natural language tasks.
1 code implementation • 21 Sep 2023 • Kai Zhang, Yangyang Kang, Fubang Zhao, Xiaozhong Liu
We contend that a mere memory module is inadequate and fully training an LLM can be excessively costly.
1 code implementation • 6 Sep 2023 • Yang Wu, Xurui Li, Xuhong Zhang, Yangyang Kang, Changlong Sun, Xiaozhong Liu
Positive-Unlabeled (PU) Learning is a challenge presented by binary classification problems where there is an abundance of unlabeled data along with a small number of positive data instances, which can be used to address chronic disease screening problem.
no code implementations • 19 Aug 2023 • Kaihang Pan, Juncheng Li, Wenjie Wang, Hao Fei, Hongye Song, Wei Ji, Jun Lin, Xiaozhong Liu, Tat-Seng Chua, Siliang Tang
Recent studies indicate that dense retrieval models struggle to perform well on a wide variety of retrieval tasks that lack dedicated training data, as different retrieval tasks often entail distinct search intents.
1 code implementation • 23 May 2023 • Xiangnan Chen, Qian Xiao, Juncheng Li, Duo Dong, Jun Lin, Xiaozhong Liu, Siliang Tang
GOSE initiates by generating preliminary relation predictions on entity pairs extracted from a scanned image of the document.
no code implementations • 22 Apr 2023 • Zilong Lin, Zhengyi Li, Xiaojing Liao, XiaoFeng Wang, Xiaozhong Liu
As a prominent instance of vandalism edits, Wiki search poisoning for illicit promotion is a cybercrime in which the adversary aims at editing Wiki articles to promote illicit businesses through Wiki search results of relevant queries.
no code implementations • 4 Apr 2023 • Yexiang Wang, Yating Zhang, Xiaozhong Liu, Changlong Sun
Because of the inevitable cost and complexity of transformer and pre-trained models, efficiency concerns are raised for long text classification.
1 code implementation • 22 Mar 2023 • Kaihang Pan, Juncheng Li, Hongye Song, Jun Lin, Xiaozhong Liu, Siliang Tang
Though effective, prompt tuning under few-shot settings on the one hand heavily relies on a good initialization of soft prompts.
no code implementations • 24 Jan 2023 • Yongqiang Ma, Jiawei Liu, Fan Yi, Qikai Cheng, Yong Huang, Wei Lu, Xiaozhong Liu
We find that there exists a "writing style" gap between AI-generated scientific text and human-written scientific text.
1 code implementation • 14 Sep 2022 • Jiawei Liu, Yangyang Kang, Di Tang, Kaisong Song, Changlong Sun, XiaoFeng Wang, Wei Lu, Xiaozhong Liu
In this study, we propose an imitation adversarial attack on black-box neural passage ranking models.
no code implementations • 7 Jun 2022 • Jiannan Guo, Yangyang Kang, Yu Duan, Xiaozhong Liu, Siliang Tang, Wenqiao Zhang, Kun Kuang, Changlong Sun, Fei Wu
Motivated by the industry practice of labeling data, we propose an innovative Inconsistency-based virtual aDvErsarial Active Learning (IDEAL) algorithm to further investigate SSL-AL's potential superiority and achieve mutual enhancement of AL and SSL, i. e., SSL propagates label information to unlabeled samples and provides smoothed embeddings for AL, while AL excludes samples with inconsistent predictions and considerable uncertainty for SSL.
no code implementations • 5 Nov 2021 • Leilei Gan, Yating Zhang, Kun Kuang, Lin Yuan, Shuo Li, Changlong Sun, Xiaozhong Liu, Fei Wu
Dialogue summarization has been extensively studied and applied, where the prior works mainly focused on exploring superior model structures to align the input dialogue and the output summary.
1 code implementation • EMNLP 2021 • Jiawei Liu, Kaisong Song, Yangyang Kang, Guoxiu He, Zhuoren Jiang, Changlong Sun, Wei Lu, Xiaozhong Liu
Chatbot is increasingly thriving in different domains, however, because of unexpected discourse complexity and training data sparseness, its potential distrust hatches vital apprehension.
1 code implementation • 20 Aug 2021 • Changzhen Ji, Yating Zhang, Xiaozhong Liu, Adam Jatowt, Changlong Sun, Conghui Zhu, Tiejun Zhao
Nevertheless, few works utilized the knowledge extracted from similar conversations for utterance generation.
no code implementations • ACL 2021 • Xiyan Fu, Yating Zhang, Tianyi Wang, Xiaozhong Liu, Changlong Sun, Zhenglu Yang
In the field of dialogue summarization, due to the lack of training data, it is often difficult for supervised summary generation methods to learn vital information from dialogue context with limited data.
1 code implementation • 12 Jul 2021 • Luyao Ma, Yating Zhang, Tianyi Wang, Xiaozhong Liu, Wei Ye, Changlong Sun, Shikun Zhang
Legal judgment prediction(LJP) is an essential task for legal AI.
1 code implementation • Findings (ACL) 2021 • Fubang Zhao, Zhuoren Jiang, Yangyang Kang, Changlong Sun, Xiaozhong Liu
Relational fact extraction aims to extract semantic triplets from unstructured text.
Ranked #6 on
Relation Extraction
on NYT
no code implementations • 13 May 2021 • Zihan Wang, Hongye Song, Zhaochun Ren, Pengjie Ren, Zhumin Chen, Xiaozhong Liu, Hongsong Li, Maarten de Rijke
First, contract elements are far more fine-grained than named entities, which hinders the transfer of extractors.
Cross-Domain Named Entity Recognition
Graph Neural Network
+5
no code implementations • 3 May 2021 • Zheng Gao, Chun Guo, Shutian Ma, Xiaozhong Liu
Therefore a heterogeneous network can be converted to a homogeneous one where those conventional methods are eligible to use.
no code implementations • 29 Apr 2021 • Yongzhen Wang, Xiaozhong Liu, Katy Börner, Jun Lin, Yingnan Ju, Changlong Sun, Luo Si
Objective: Ubiquitous internet access is reshaping the way we live, but it is accompanied by unprecedented challenges in preventing chronic diseases that are usually planted by long exposure to unhealthy lifestyles.
no code implementations • 27 Mar 2021 • Zhuoren Jiang, Xiaozhong Liu, Liangcai Gao, Zhi Tang
Although the content in scientific publications is increasingly challenging, it is necessary to investigate another important problem, that of scientific information understanding.
no code implementations • 10 Feb 2021 • Qiao Jin, Zheng Yuan, Guangzhi Xiong, Qianlan Yu, Huaiyuan Ying, Chuanqi Tan, Mosha Chen, Songfang Huang, Xiaozhong Liu, Sheng Yu
Automatic Question Answering (QA) has been successfully applied in various domains such as search engines and chatbots.
no code implementations • 19 Jan 2021 • Shutian Ma, Heng Zhang, Chengzhi Zhang, Xiaozhong Liu
Citation recommendation is an important task to assist scholars in finding candidate literature to cite.
1 code implementation • 14 Dec 2020 • Yicheng Zou, Jun Lin, Lujun Zhao, Yangyang Kang, Zhuoren Jiang, Changlong Sun, Qi Zhang, Xuanjing Huang, Xiaozhong Liu
Automatic chat summarization can help people quickly grasp important information from numerous chat messages.
1 code implementation • 14 Dec 2020 • Yicheng Zou, Lujun Zhao, Yangyang Kang, Jun Lin, Minlong Peng, Zhuoren Jiang, Changlong Sun, Qi Zhang, Xuanjing Huang, Xiaozhong Liu
In a customer service system, dialogue summarization can boost service efficiency by automatically creating summaries for long spoken dialogues in which customers and agents try to address issues about specific topics.
2 code implementations • 14 Dec 2020 • Jiawei Liu, Zhe Gao, Yangyang Kang, Zhuoren Jiang, Guoxiu He, Changlong Sun, Xiaozhong Liu, Wei Lu
Is chatbot able to completely replace the human agent?
no code implementations • Findings of the Association for Computational Linguistics 2020 • WeiSheng Zhang, Kaisong Song, Yangyang Kang, Zhongqing Wang, Changlong Sun, Xiaozhong Liu, Shoushan Li, Min Zhang, Luo Si
As an important research topic, customer service dialogue generation tends to generate generic seller responses by leveraging current dialogue information.
1 code implementation • EMNLP 2020 • Changzhen Ji, Xin Zhou, Yating Zhang, Xiaozhong Liu, Changlong Sun, Conghui Zhu, Tiejun Zhao
In the past few years, audiences from different fields witness the achievements of sequence-to-sequence models (e. g., LSTM+attention, Pointer Generator Networks, and Transformer) to enhance dialogue content generation.
1 code implementation • EMNLP 2020 • Qiao Jin, Chuanqi Tan, Mosha Chen, Xiaozhong Liu, Songfang Huang
In the CTRP framework, a model takes a PICO-formatted clinical trial proposal with its background as input and predicts the result, i. e. how the Intervention group compares with the Comparison group in terms of the measured Outcome in the studied Population.
no code implementations • 6 Sep 2020 • Zheng Gao, Hongsong Li, Zhuoren Jiang, Xiaozhong Liu
In this paper, our model, Pairwise Cross-graph Community Detection (PCCD), is proposed to cope with the sparse graph problem by involving external graph knowledge to learn user pairwise community closeness instead of detecting direct communities.
no code implementations • 6 Sep 2020 • Zheng Gao, Chun Guo, Xiaozhong Liu
Personalized community detection aims to generate communities associated with user need on graphs, which benefits many downstream tasks such as node recommendation and link prediction for users, etc.
no code implementations • ACL 2020 • Zhuoren Jiang, Zhe Gao, Yu Duan, Yangyang Kang, Changlong Sun, Qiong Zhang, Xiaozhong Liu
We propose a Semi-supervIsed GeNerative Active Learning (SIGNAL) model to address the imbalance, efficiency, and text camouflage problems of Chinese text spam detection task.
no code implementations • 24 Jun 2020 • Guoqing Zhu, Naga Anjaneyulu Kopalle, Yongzhen Wang, Xiaozhong Liu, Kemi Jona, Katy Börner
How does your education impact your professional career?
1 code implementation • 17 May 2020 • Juntao Li, Chang Liu, Jian Wang, Lidong Bing, Hongsong Li, Xiaozhong Liu, Dongyan Zhao, Rui Yan
We manually collect a new and high-quality paired dataset, where each pair contains an unordered product attribute set in the source language and an informative product description in the target language.
2 code implementations • 27 Feb 2020 • Tianyi Wang, Yating Zhang, Xiaozhong Liu, Changlong Sun, Qiong Zhang
Multi-role dialogue understanding comprises a wide range of diverse tasks such as question answering, act classification, dialogue summarization etc.
no code implementations • 3 Jan 2020 • Guoxiu He, Zhe Gao, Zhuoren Jiang, Yangyang Kang, Changlong Sun, Xiaozhong Liu, Wei Lu
The nonliteral interpretation of a text is hard to be understood by machine models due to its high context-sensitivity and heavy usage of figurative language.
no code implementations • IJCNLP 2019 • Kaisong Song, Lidong Bing, Wei Gao, Jun Lin, Lujun Zhao, Jiancheng Wang, Changlong Sun, Xiaozhong Liu, Qiong Zhang
Customers ask questions and customer service staffs answer their questions, which is the basic service model via multi-turn customer service (CS) dialogues on E-commerce platforms.
no code implementations • IJCNLP 2019 • Yingchi Liu, Quanzhi Li, Marika Cifor, Xiaozhong Liu, Qiong Zhang, Luo Si
Sexual harassment occurred in a variety of situations, and categorization of the stories and extraction of their key elements will provide great help for the related parties to understand and address sexual harassment.
no code implementations • IJCNLP 2019 • Jingjing Wang, Changlong Sun, Shoushan Li, Jiancheng Wang, Luo Si, Min Zhang, Xiaozhong Liu, Guodong Zhou
This approach incorporates clause selection and word selection strategies to tackle the data noise problem in the task of DASC.
1 code implementation • 30 Aug 2019 • Zhuoren Jiang, Jian Wang, Lujun Zhao, Changlong Sun, Yao Lu, Xiaozhong Liu
Aspect category detection is an essential task for sentiment analysis and opinion mining.
1 code implementation • IJCNLP 2019 • Zhuoren Jiang, Zhe Gao, Guoxiu He, Yangyang Kang, Changlong Sun, Qiong Zhang, Luo Si, Xiaozhong Liu
The VFGE can learn both the graph embeddings of the Chinese characters (local) and the latent variation families (global).
Ranked #1 on
Chinese Spam Detection
on SMS
no code implementations • 12 Jul 2019 • Zheng Gao, Lin Guo, Chi Ma, Xiao Ma, Kai Sun, Hang Xiang, Xiaoqiang Zhu, Hongsong Li, Xiaozhong Liu
Anomaly detection is facing with emerging challenges in many important industry domains, such as cyber security and online recommendation and advertising.
no code implementations • ACL 2019 • Jingjing Wang, Changlong Sun, Shoushan Li, Xiaozhong Liu, Luo Si, Min Zhang, Guodong Zhou
This paper extends the research to interactive reviews and proposes a new research task, namely Aspect Sentiment Classification towards Question-Answering (ASC-QA), for real-world applications.
1 code implementation • EMNLP 2018 • Yongzhen Wang, Xiaozhong Liu, Zheng Gao
Conventional solutions to automatic related work summarization rely heavily on human-engineered features.
1 code implementation • 31 Dec 2018 • Zhuoren Jiang, Yue Yin, Liangcai Gao, Yao Lu, Xiaozhong Liu
While the volume of scholarly publications has increased at a frenetic pace, accessing and consuming the useful candidate papers, in very large digital libraries, is becoming an essential and challenging task for scholars.
no code implementations • EMNLP 2018 • Chenlin Shen, Changlong Sun, Jingjing Wang, Yangyang Kang, Shoushan Li, Xiaozhong Liu, Luo Si, Min Zhang, Guodong Zhou
On the basis, we propose a three-stage hierarchical matching network to explore deep sentiment information in a QA text pair.
1 code implementation • 7 Sep 2018 • Zheng Gao, Gang Fu, Chunping Ouyang, Satoshi Tsutsui, Xiaozhong Liu, Jeremy Yang, Christopher Gessner, Brian Foote, David Wild, Qi Yu, Ying Ding
We propose this method for its added value relative to existing graph analytical methodology, and in the real world context of biomedical knowledge discovery applicability.
no code implementations • COLING 2018 • Lu Wang, Shoushan Li, Changlong Sun, Luo Si, Xiaozhong Liu, Min Zhang, Guodong Zhou
Question-Answer (QA) matching is a fundamental task in the Natural Language Processing community.