51 citations · 107 across the 33 of their papers we have counts for
22 papers · 1 filter
Intelligent Legal Assistant: An Interactive Clarification System for Legal Question Answering
Rujing Yao, Yiquan Wu, Tong Zhang +7
The rise of large language models has opened new avenues for users seeking legal advice. However, users often lack professional legal knowledge, which can lead to questions that om…
A Speaker Turn-Aware Multi-Task Adversarial Network for Joint User Satisfaction Estimation and Sentiment Analysis
Kaisong Song, Yangyang Kang, Jiawei Liu +3
User Satisfaction Estimation is an important task and increasingly being applied in goal-oriented dialogue systems to estimate whether the user is satisfied with the service. It is…
Enhance Robustness of Language Models Against Variation Attack through Graph Integration
Zi Xiong, Lizhi Qing, Yangyang Kang +5
The widespread use of pre-trained language models (PLMs) in natural language processing (NLP) has greatly improved performance outcomes. However, these models' vulnerability to adv…
Evolving Knowledge Distillation with Large Language Models and Active Learning
Chengyuan Liu, Yangyang Kang, Fubang Zhao +4
Large language models (LLMs) have demonstrated remarkable capabilities across various NLP tasks. However, their computational costs are prohibitively high. To address this issue, p…
Precedent-Enhanced Legal Judgment Prediction with LLM and Domain-Model Collaboration
Yiquan Wu, Siying Zhou, Yifei Liu +6
Legal Judgment Prediction (LJP) has become an increasingly crucial task in Legal AI, i.e., predicting the judgment of the case in terms of case fact description. Precedents are the…
Goal-Oriented Prompt Attack and Safety Evaluation for LLMs
Chengyuan Liu, Fubang Zhao, Lizhi Qing +4
Large Language Models (LLMs) presents significant priority in text understanding and generation. However, LLMs suffer from the risk of generating harmful contents especially while…
Multidimensional Perceptron for Efficient and Explainable Long Text Classification
Yexiang Wang, Yating Zhang, Xiaozhong Liu +1
Because of the inevitable cost and complexity of transformer and pre-trained models, efficiency concerns are raised for long text classification. Meanwhile, in the highly sensitive…
RexUIE: A Recursive Method with Explicit Schema Instructor for Universal Information Extraction
Chengyuan Liu, Fubang Zhao, Yangyang Kang +5
Universal Information Extraction (UIE) is an area of interest due to the challenges posed by varying targets, heterogeneous structures, and demand-specific schemas. However, previo…
Dialogue Inspectional Summarization with Factual Inconsistency Awareness
Leilei Gan, Yating Zhang, Kun Kuang +5
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 out…
A Role-Selected Sharing Network for Joint Machine-Human Chatting Handoff and Service Satisfaction Analysis
Jiawei Liu, Kaisong Song, Yangyang Kang +5
Chatbot is increasingly thriving in different domains, however, because of unexpected discourse complexity and training data sparseness, its potential distrust hatches vital appreh…
A Neural Conversation Generation Model via Equivalent Shared Memory Investigation
Changzhen Ji, Yating Zhang, Xiaozhong Liu +4
Conversation generation as a challenging task in Natural Language Generation (NLG) has been increasingly attracting attention over the last years. A number of recent works adopted…
Legal Judgment Prediction with Multi-Stage CaseRepresentation Learning in the Real Court Setting
Luyao Ma, Yating Zhang, Tianyi Wang +4
Legal judgment prediction(LJP) is an essential task for legal AI. While prior methods studied on this topic in a pseudo setting by employing the judge-summarized case narrative as…
Adjacency List Oriented Relational Fact Extraction via Adaptive Multi-task Learning
Fubang Zhao, Zhuoren Jiang, Yangyang Kang +2
Relational fact extraction aims to extract semantic triplets from unstructured text. In this work, we show that all of the relational fact extraction models can be organized accord…
Time to Transfer: Predicting and Evaluating Machine-Human Chatting Handoff
Jiawei Liu, Zhe Gao, Yangyang Kang +5
Is chatbot able to completely replace the human agent? The short answer could be - "it depends...". For some challenging cases, e.g., dialogue's topical spectrum spreads beyond the…
Topic-Oriented Spoken Dialogue Summarization for Customer Service with Saliency-Aware Topic Modeling
Yicheng Zou, Lujun Zhao, Yangyang Kang +7
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…
Unsupervised Summarization for Chat Logs with Topic-Oriented Ranking and Context-Aware Auto-Encoders
Yicheng Zou, Jun Lin, Lujun Zhao +6
Automatic chat summarization can help people quickly grasp important information from numerous chat messages. Unlike conventional documents, chat logs usually have fragmented and e…
Cross Copy Network for Dialogue Generation
Changzhen Ji, Xin Zhou, Yating Zhang +4
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) t…
Masking Orchestration: Multi-task Pretraining for Multi-role Dialogue Representation Learning
Tianyi Wang, Yating Zhang, Xiaozhong Liu +2
Multi-role dialogue understanding comprises a wide range of diverse tasks such as question answering, act classification, dialogue summarization etc. While dialogue corpora are abu…
Read Beyond the Lines: Understanding the Implied Textual Meaning via a Skim and Intensive Reading Model
Guoxiu He, Zhe Gao, Zhuoren Jiang +4
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. In this study, inspir…
Human-Like Decision Making: Document-level Aspect Sentiment Classification via Hierarchical Reinforcement Learning
Jingjing Wang, Changlong Sun, Shoushan Li +5
Recently, neural networks have shown promising results on Document-level Aspect Sentiment Classification (DASC). However, these approaches often offer little transparency w.r.t. th…
Cross-domain Aspect Category Transfer and Detection via Traceable Heterogeneous Graph Representation Learning
Zhuoren Jiang, Jian Wang, Lujun Zhao +3
Aspect category detection is an essential task for sentiment analysis and opinion mining. However, the cost of categorical data labeling, e.g., label the review aspect information…
Detect Camouflaged Spam Content via StoneSkipping: Graph and Text Joint Embedding for Chinese Character Variation Representation
Zhuoren Jiang, Zhe Gao, Guoxiu He +5
The task of Chinese text spam detection is very challenging due to both glyph and phonetic variations of Chinese characters. This paper proposes a novel framework to jointly model…