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20242026
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cs.CL2026

Counting on Consensus: Selecting the Right Inter-annotator Agreement Metric for NLP Annotation and Evaluation

Joseph James

Human annotation remains the foundation of reliable and interpretable data in Natural Language Processing (NLP). As annotation and evaluation tasks continue to expand, from categor…

cs.CL2026

Evaluating LLM-Based Grant Proposal Review via Structured Perturbations

William Thorne, Joseph James, Yang Wang +2

As AI-assisted grant proposals outpace manual review capacity in a kind of ``Malthusian trap'' for the research ecosystem, this paper investigates the capabilities and limitations…

cs.CL2026

RIGOURATE: Quantifying Scientific Exaggeration with Evidence-Aligned Claim Evaluation

Joseph James, Chenghao Xiao, Yucheng Li +2

Scientific rigour tends to be sidelined in favour of bold statements, leading authors to overstate claims beyond what their results support. We present RIGOURATE, a two-stage multi…

cs.CL2025

Seeing isn't Hearing: Benchmarking Vision Language Models at Interpreting Spectrograms

Tyler Loakman, Joseph James, Chenghua Lin

With the rise of Large Language Models (LLMs) and their vision-enabled counterparts (VLMs), numerous works have investigated their capabilities in tasks that fuse the modalities of…

cs.CL2024

On the Rigour of Scientific Writing: Criteria, Analysis, and Insights

Joseph James, Chenghao Xiao, Yucheng Li +1

Rigour is crucial for scientific research as it ensures the reproducibility and validity of results and findings. Despite its importance, little work exists on modelling rigour com…