14 citations · 22 across the 8 of their papers we have counts for
6 papers · 1 filter
LoRM: Learning the Language of Rotating Machinery for Self-Supervised Condition Monitoring
Xiao Qin, Xingyi Song, Tong Liu +4
We present LoRM (Language of Rotating Machinery), a self-supervised framework for multi-modal rotating-machinery signal understanding and real-time condition monitoring. LoRM is bu…
ESG-Bench: Benchmarking Long-Context ESG Reports for Hallucination Mitigation
Siqi Sun, Ben Peng Wu, Mali Jin +3
As corporate responsibility increasingly incorporates environmental, social, and governance (ESG) criteria, ESG reporting is becoming a legal requirement in many regions and a key…
A Dataset for Analysing News Framing in Chinese Media
Owen Cook, Yida Mu, Xinye Yang +2
Framing is an essential device in news reporting, allowing the writer to influence public perceptions of current affairs. While there are existing automatic news framing detection…
Addressing Topic Granularity and Hallucination in Large Language Models for Topic Modelling
Yida Mu, Peizhen Bai, Kalina Bontcheva +1
Large language models (LLMs) with their strong zero-shot topic extraction capabilities offer an alternative to probabilistic topic modelling and closed-set topic classification app…
Large Language Models Offer an Alternative to the Traditional Approach of Topic Modelling
Yida Mu, Chun Dong, Kalina Bontcheva +1
Topic modelling, as a well-established unsupervised technique, has found extensive use in automatically detecting significant topics within a corpus of documents. However, classic…
Don't Waste a Single Annotation: Improving Single-Label Classifiers Through Soft Labels
Ben Wu, Yue Li, Yida Mu +3
In this paper, we address the limitations of the common data annotation and training methods for objective single-label classification tasks. Typically, when annotating such tasks…