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20232025
most citedLarge Language Models are Inconsistent and Biased Evaluators

12 citations · 22 across the 9 of their papers we have counts for

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5 papers · 1 filter

cs.CL2024

MatViX: Multimodal Information Extraction from Visually Rich Articles

Ghazal Khalighinejad, Sharon Scott, Ollie Liu +4

Multimodal information extraction (MIE) is crucial for scientific literature, where valuable data is often spread across text, figures, and tables. In materials science, extracting…

cs.CL2024★ 1 cited

Your Large Language Models Are Leaving Fingerprints

Hope McGovern, Rickard Stureborg, Yoshi Suhara +1

It has been shown that finetuned transformers and other supervised detectors effectively distinguish between human and machine-generated text in some situations arXiv:2305.13242, b…

cs.CL2024★ 12 cited

Large Language Models are Inconsistent and Biased Evaluators

Rickard Stureborg, Dimitris Alikaniotis, Yoshi Suhara

The zero-shot capability of Large Language Models (LLMs) has enabled highly flexible, reference-free metrics for various tasks, making LLM evaluators common tools in NLP. However,…

cs.CL2024

Tailoring Vaccine Messaging with Common-Ground Opinions

Rickard Stureborg, Sanxing Chen, Ruoyu Xie +6

One way to personalize chatbot interactions is by establishing common ground with the intended reader. A domain where establishing mutual understanding could be particularly impact…

cs.CL2024

Hierarchical Multi-Label Classification of Online Vaccine Concerns

Chloe Qinyu Zhu, Rickard Stureborg, Bhuwan Dhingra

Vaccine concerns are an ever-evolving target, and can shift quickly as seen during the COVID-19 pandemic. Identifying longitudinal trends in vaccine concerns and misinformation mig…