3 articles tagged with #citation-analysis. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.
Researchers have developed APRES, an AI-powered system that uses Large Language Models to automatically revise scientific papers based on evaluation rubrics that predict citation counts. The system improves citation prediction accuracy by 19.6% and produces paper revisions that human experts prefer 79% of the time over original versions.
Researchers introduced SciTrek, a new benchmark for testing large language models' ability to perform numerical reasoning across long scientific documents. The benchmark reveals significant challenges for current LLMs, with the best model achieving only 46.5% accuracy at 128K tokens, and performance declining as context length increases.
Researchers tested GPT-5's ability to perform citation context analysis by examining how different prompt designs affect the model's interpretative readings of academic citations. The study found that while GPT-5 produces consistent surface classifications, prompt scaffolding significantly influences which interpretative frameworks and vocabularies the model emphasizes in deeper analysis.
