153 citations · 387 across the 20 of their papers we have counts for
21 papers
Credibility Governance: A Social Mechanism for Collective Self-Correction under Weak Truth Signals
Wanying He, Yanxi Lin, Ziheng Zhou +5
Online platforms increasingly rely on opinion aggregation to allocate real-world attention and resources, yet common signals such as engagement votes or capital-weighted commitment…
Overview of the BioLaySumm 2023 Shared Task on Lay Summarization of Biomedical Research Articles
Tomas Goldsack, Zheheng Luo, Qianqian Xie +4
This paper presents the results of the shared task on Lay Summarisation of Biomedical Research Articles (BioLaySumm), hosted at the BioNLP Workshop at ACL 2023. The goal of this sh…
MentaLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language Models
Kailai Yang, Tianlin Zhang, Ziyan Kuang +3
With the development of web technology, social media texts are becoming a rich source for automatic mental health analysis. As traditional discriminative methods bear the problem o…
LongDocFACTScore: Evaluating the Factuality of Long Document Abstractive Summarisation
Jennifer A Bishop, Qianqian Xie, Sophia Ananiadou
Maintaining factual consistency is a critical issue in abstractive text summarisation, however, it cannot be assessed by traditional automatic metrics used for evaluating text summ…
Graph Contrastive Topic Model
Zheheng Luo, Lei Liu, Qianqian Xie +1
Existing NTMs with contrastive learning suffer from the sample bias problem owing to the word frequency-based sampling strategy, which may result in false negative samples with sim…
A scoping review on multimodal deep learning in biomedical images and texts
Zhaoyi Sun, Mingquan Lin, Qingqing Zhu +4
Computer-assisted diagnostic and prognostic systems of the future should be capable of simultaneously processing multimodal data. Multimodal deep learning (MDL), which involves the…
PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance
Qianqian Xie, Weiguang Han, Xiao Zhang +4
Although large language models (LLMs) has shown great performance on natural language processing (NLP) in the financial domain, there are no publicly available financial tailtored…
Word Grounded Graph Convolutional Network
Zhibin Lu, Qianqian Xie, Benyou Wang +1
Graph Convolutional Networks (GCNs) have shown strong performance in learning text representations for various tasks such as text classification, due to its expressive power in mod…
The Wall Street Neophyte: A Zero-Shot Analysis of ChatGPT Over MultiModal Stock Movement Prediction Challenges
Qianqian Xie, Weiguang Han, Yanzhao Lai +2
Recently, large language models (LLMs) like ChatGPT have demonstrated remarkable performance across a variety of natural language processing tasks. However, their effectiveness in…
ChatGPT as a Factual Inconsistency Evaluator for Text Summarization
Zheheng Luo, Qianqian Xie, Sophia Ananiadou
The performance of text summarization has been greatly boosted by pre-trained language models. A main concern of existing methods is that most generated summaries are not factually…
Zero-shot Temporal Relation Extraction with ChatGPT
Chenhan Yuan, Qianqian Xie, Sophia Ananiadou
The goal of temporal relation extraction is to infer the temporal relation between two events in the document. Supervised models are dominant in this task. In this work, we investi…
A Survey for Biomedical Text Summarization: From Pre-trained to Large Language Models
Qianqian Xie, Zheheng Luo, Benyou Wang +1
The exponential growth of biomedical texts such as biomedical literature and electronic health records (EHRs), poses a significant challenge for clinicians and researchers to acces…
Mastering Pair Trading with Risk-Aware Recurrent Reinforcement Learning
Weiguang Han, Jimin Huang, Qianqian Xie +3
Although pair trading is the simplest hedging strategy for an investor to eliminate market risk, it is still a great challenge for reinforcement learning (RL) methods to perform pa…
FactReranker: Fact-guided Reranker for Faithful Radiology Report Summarization
Qianqian Xie, Jiayu Zhou, Yifan Peng +1
Automatic radiology report summarization is a crucial clinical task, whose key challenge is to maintain factual accuracy between produced summaries and ground truth radiology findi…
CitationSum: Citation-aware Graph Contrastive Learning for Scientific Paper Summarization
Zheheng Luo, Qianqian Xie, Sophia Ananiadou
Citation graphs can be helpful in generating high-quality summaries of scientific papers, where references of a scientific paper and their correlations can provide additional knowl…
Select and Trade: Towards Unified Pair Trading with Hierarchical Reinforcement Learning
Weiguang Han, Boyi Zhang, Qianqian Xie +3
Pair trading is one of the most effective statistical arbitrage strategies which seeks a neutral profit by hedging a pair of selected assets. Existing methods generally decompose t…
SMiLE: Schema-augmented Multi-level Contrastive Learning for Knowledge Graph Link Prediction
Miao Peng, Ben Liu, Qianqian Xie +3
Link prediction is the task of inferring missing links between entities in knowledge graphs. Embedding-based methods have shown effectiveness in addressing this problem by modeling…
Readability Controllable Biomedical Document Summarization
Zheheng Luo, Qianqian Xie, Sophia Ananiadou
Different from general documents, it is recognised that the ease with which people can understand a biomedical text is eminently varied, owing to the highly technical nature of bio…
GRETEL: Graph Contrastive Topic Enhanced Language Model for Long Document Extractive Summarization
Qianqian Xie, Jimin Huang, Tulika Saha +1
Recently, neural topic models (NTMs) have been incorporated into pre-trained language models (PLMs), to capture the global semantic information for text summarization. However, in…
Can Language Models Make Fun? A Case Study in Chinese Comical Crosstalk
Benyou Wang, Xiangbo Wu, Xiaokang Liu +3
Language is the principal tool for human communication, in which humor is one of the most attractive parts. Producing natural language like humans using computers, a.k.a, Natural L…
MLR: A Two-stage Conversational Query Rewriting Model with Multi-task Learning
Shuangyong Song, Chao Wang, Qianqian Xie +3
Conversational context understanding aims to recognize the real intention of user from the conversation history, which is critical for building the dialogue system. However, the mu…