Episode Details

In this month’s episode of The Cisco AI Insights Podcast, hosts Rafael Herrera and Sónia Marques explore the evolving landscape of sentiment analysis with Cisco machine learning engineer Joan Rossello. The conversation centers on the research paper from Imperial College London, “FinDPO: Financial Sentiment Analysis for Algorithmic Trading Through Preference Optimization of LLMs,” which proposes a new way to train large language models to better interpret nuanced human language. By comparing output quality, this preference-based training improved generalization and helped models interpret complex financial language without relying on simple memorization. Additionally, the discussion explored how sentiment scores derived from model probabilities were used to rank companies based on the strength of their news coverage, yielding promising results. A special thank you to the team that developed this month's paper. If you are interested in reading the paper yourself, please visit this link: ⁠ https://arxiv.org/abs/2507.18417