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Auditing LLMs and Twitter

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Manage episode 463853652 series 1361404
Content provided by Kyle Polich. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Kyle Polich or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

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

  continue reading

572 episodes

Artwork

Auditing LLMs and Twitter

Data Skeptic

281 subscribers

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Manage episode 463853652 series 1361404
Content provided by Kyle Polich. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Kyle Polich or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

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

  continue reading

572 episodes

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