113 citations · 368 across the 39 of their papers we have counts for
15 papers · 1 filter
MemoChat: Tuning LLMs to Use Memos for Consistent Long-Range Open-Domain Conversation
Junru Lu, Siyu An, Mingbao Lin +5
We propose MemoChat, a pipeline for refining instructions that enables large language models (LLMs) to effectively employ self-composed memos for maintaining consistent long-range…
CUE: An Uncertainty Interpretation Framework for Text Classifiers Built on Pre-Trained Language Models
Jiazheng Li, Zhaoyue Sun, Bin Liang +2
Text classifiers built on Pre-trained Language Models (PLMs) have achieved remarkable progress in various tasks including sentiment analysis, natural language inference, and questi…
Document-Level Multi-Event Extraction with Event Proxy Nodes and Hausdorff Distance Minimization
Xinyu Wang, Lin Gui, Yulan He
Document-level multi-event extraction aims to extract the structural information from a given document automatically. Most recent approaches usually involve two steps: (1) modeling…
Cone: Unsupervised Contrastive Opinion Extraction
Runcong Zhao, Lin Gui, Yulan He
Contrastive opinion extraction aims to extract a structured summary or key points organised as positive and negative viewpoints towards a common aspect or topic. Most recent works…
Event Knowledge Incorporation with Posterior Regularization for Event-Centric Question Answering
Junru Lu, Gabriele Pergola, Lin Gui +1
We propose a simple yet effective strategy to incorporate event knowledge extracted from event trigger annotations via posterior regularization to improve the event reasoning capab…
NewsQuote: A Dataset Built on Quote Extraction and Attribution for Expert Recommendation in Fact-Checking
Wenjia Zhang, Lin Gui, Rob Procter +1
To enhance the ability to find credible evidence in news articles, we propose a novel task of expert recommendation, which aims to identify trustworthy experts on a specific news t…
Distilling ChatGPT for Explainable Automated Student Answer Assessment
Jiazheng Li, Lin Gui, Yuxiang Zhou +3
Providing explainable and faithful feedback is crucial for automated student answer assessment. In this paper, we introduce a novel framework that explores using ChatGPT, a cutting…
Explainable Recommender with Geometric Information Bottleneck
Hanqi Yan, Lin Gui, Menghan Wang +2
Explainable recommender systems can explain their recommendation decisions, enhancing user trust in the systems. Most explainable recommender systems either rely on human-annotated…
Some Observations on Fact-Checking Work with Implications for Computational Support
Rob Procter, Miguel Arana-Catania, Yulan He +4
Social media and user-generated content (UGC) have become increasingly important features of journalistic work in a number of different ways. However, the growth of misinformation…
A User-Centered, Interactive, Human-in-the-Loop Topic Modelling System
Zheng Fang, Lama Alqazlan, Du Liu +2
Human-in-the-loop topic modelling incorporates users' knowledge into the modelling process, enabling them to refine the model iteratively. Recent research has demonstrated the valu…
PANACEA: An Automated Misinformation Detection System on COVID-19
Runcong Zhao, Miguel Arana-Catania, Lixing Zhu +6
In this demo, we introduce a web-based misinformation detection system PANACEA on COVID-19 related claims, which has two modules, fact-checking and rumour detection. Our fact-check…
NapSS: Paragraph-level Medical Text Simplification via Narrative Prompting and Sentence-matching Summarization
Junru Lu, Jiazheng Li, Byron C. Wallace +2
Accessing medical literature is difficult for laypeople as the content is written for specialists and contains medical jargon. Automated text simplification methods offer a potenti…
Event Temporal Relation Extraction with Bayesian Translational Model
Xingwei Tan, Gabriele Pergola, Yulan He
Existing models to extract temporal relations between events lack a principled method to incorporate external knowledge. In this study, we introduce Bayesian-Trans, a Bayesian lear…
Distinguishability Calibration to In-Context Learning
Hongjing Li, Hanqi Yan, Yanran Li +3
Recent years have witnessed increasing interests in prompt-based learning in which models can be trained on only a few annotated instances, making them suitable in low-resource set…
Tracking Brand-Associated Polarity-Bearing Topics in User Reviews
Runcong Zhao, Lin Gui, Hanqi Yan +1
Monitoring online customer reviews is important for business organisations to measure customer satisfaction and better manage their reputations. In this paper, we propose a novel d…