Three Concrete Challenges and Two Hopes for the Safety of Unsupervised Elicitation | ScienceToStartup | ScienceToStartup

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References (42)

[1]

PolBiX: Detecting LLMs' Political Bias in Fact-Checking through X-phemisms

2025Charlott Jakob, David Harbecke et al.

[2]

Probing the Geometry of Truth: Consistency and Generalization of Truth Directions in LLMs Across Logical Transformations and Question Answering Tasks

2025Yuntai Bao, Xuhong Zhang et al.

[3]

Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation

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Three Concrete Challenges and Two Hopes for the Safety of Unsupervised Elicitation

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References (42)

Founder's Pitch

"Develop robust unsupervised elicitation techniques to improve the reliability of language models on challenging datasets."

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Three Concrete Challenges and Two Hopes for the Safety of Unsupervised Elicitation

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References (42)

Founder's Pitch

"Develop robust unsupervised elicitation techniques to improve the reliability of language models on challenging datasets."

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