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20242026
most citedThe Hot Mess of AI: How Does Misalignment Scale With Model Intelligence and Task Complexity?

1 citations · 1 across the 3 of their papers we have counts for

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cs.CL2026

Stabilizing Efficient Reasoning with Step-Level Advantage Selection

Han Wang, Xiaodong Yu, Jialian Wu +4

Large language models (LLMs) achieve strong reasoning performance by allocating substantial computation at inference time, often generating long and verbose reasoning traces. While…

cs.CL2026

Unsupervised Elicitation of Language Models

Jiaxin Wen, Zachary Ankner, Arushi Somani +10

To steer pretrained language models for downstream tasks, today's post-training paradigm relies on humans to specify desired behaviors. However, for models with superhuman capabili…

cs.CL2025

Persona Vectors: Monitoring and Controlling Character Traits in Language Models

Runjin Chen, Andy Arditi, Henry Sleight +2

Large language models interact with users through a simulated 'Assistant' persona. While the Assistant is typically trained to be helpful, harmless, and honest, it sometimes deviat…

cs.CL2024

Best-of-N Jailbreaking

John Hughes, Sara Price, Aengus Lynch +7

We introduce Best-of-N (BoN) Jailbreaking, a simple black-box algorithm that jailbreaks frontier AI systems across modalities. BoN Jailbreaking works by repeatedly sampling variati…

cs.CL2024

Failures to Find Transferable Image Jailbreaks Between Vision-Language Models

Rylan Schaeffer, Dan Valentine, Luke Bailey +12

The integration of new modalities into frontier AI systems offers exciting capabilities, but also increases the possibility such systems can be adversarially manipulated in undesir…

cs.CL2024

Adaptive Deployment of Untrusted LLMs Reduces Distributed Threats

Jiaxin Wen, Vivek Hebbar, Caleb Larson +9

As large language models (LLMs) become increasingly capable, it is prudent to assess whether safety measures remain effective even if LLMs intentionally try to bypass them. Previou…