The Geometry of Truth: Emergent Linear Structure in LLM Representation of True/False Datasets

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Richard (Kudo) Couto: The Hidden Horror Behind a Billion-Dollar Brand 42:18

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“I used to be the largest dairy consumer on the planet. I used to eat so much dairy and meat. The more that I looked into the dairy industry, the more that I saw that it was the singular, most inhumane industry on the planet, that we've all been lied to, including myself, for years. I always believed that the picture on the milk carton, the cow standing next to her calf in the green field with the red barn in the back was true. It’s certainly the complete opposite.” – Richard (Kudo) Couto Richard (Kudo) Couto is the founder of Animal Recovery Mission (ARM), an organization solely dedicated to investigating extreme animal cruelty cases. ARM has led high-risk undercover operations that have resulted in the shutdown of illegal slaughterhouses, animal fighting rings, and horse meat trafficking networks. Recently, they released a damning investigation into two industrial dairy farms outside of Phoenix, Arizona supplying milk to Coca-Cola’s Fairlife brand. What they uncovered was systemic animal abuse, environmental violations, and a devastating betrayal of consumer trust. While Fairlife markets its products as being sourced "humanely," ARM’s footage tells a very different story—one of suffering, abuse, and corporate complicity. Despite the evidence, this story has been largely ignored by mainstream media—likely due to Coca-Cola’s massive influence and advertising dollars.…

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For this paper read, we’re joined by Samuel Marks, Postdoctoral Research Associate at Northeastern University, to discuss his paper, “The Geometry of Truth: Emergent Linear Structure in LLM Representation of True/False Datasets.” Samuel and his team curated high-quality datasets of true/false statements and used them to study in detail the structure of LLM representations of truth. Overall, they present evidence that language models linearly represent the truth or falsehood of factual statements and also introduce a novel technique, mass-mean probing, which generalizes better and is more causally implicated in model outputs than other probing techniques.
Find the transcript and read more here: https://arize.com/blog/the-geometry-of-truth-emergent-linear-structure-in-llm-representation-of-true-false-datasets-paper-reading/

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The Geometry of Truth: Emergent Linear Structure in LLM Representation of True/False Datasets

Deep Papers

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Learn more about AI observability and evaluation, join the Arize AI Slack community or get the latest on LinkedIn and X.

49 قسمت

#Science #Tech #Math #Business #Arize AI

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The Geometry of Truth: Emergent Linear Structure in LLM Representation of True/False Datasets