Episode
Auditing LLMs and Twitter
- Podcast
- Data Skeptic
- Published
- Jan 29, 2025
- Duration seconds
- 2426
- Processing state
failed
Actions
POST https://stenobird.com/v1/public/podcasts/data-skeptic/episodes/auditing-llms-and-twitter/transcription-requests
Idempotently request low-priority transcript generation for this episode.GET https://stenobird.com/podcast/data-skeptic/auditing-llms-and-twitter.md
Read the agent-friendly Markdown representation of this episode resource.
Summary
Our guests, Erwan Le Merrer and Gilles Tredan, are long-time collaborators in graph theory and distributed systems. They share their expertise on applying graph-based approaches to understanding both large language model (LLM) hallucinations and shadow banning on social media platforms. In this episode, listeners will learn how graph structures and metrics can reveal patterns in algorithmic behavior and platform moderation practices. Key insights include the use of graph theory to evaluate LLM outputs, uncovering patterns in hallucinated graphs that might hint at the underlying structure and training data of the models, and applying epidemic models to analyze the uneven spread of shadow banning on Twitter. ------------------------------- Want to listen ad-free? Try our Graphs Course? Join Data Skeptic+ for $5 / month of $50 / year https://plus.dataskeptic.com