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LLM alignment

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2 articles Professional Briefings Operator-Focused

Frontier Signal

Foresighted Policy Optimization Prevents RLHF Alignment Collapse

New research introduces Foresighted Policy Optimization (FPO) to prevent alignment collapse in iterative RLHF, addressing how LLMs exploit reward model blind spots.

May 7, 2026 6 min read Siegfried Kamgo

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Abstract digital illustration of an AI feedback loop, with data flowing between a central neural network and human feedback icons, representing iterative RLHF.

Abstract depiction of glowing neural network pathways representing specific behavioral circuits within an LLM.

Frontier Signal

arXiv: Perturbation Probing Reveals LLM Behavioral Circuits

Perturbation Probing, a new diagnostic technique, identifies specific FFN neuron circuits controlling LLM behaviors like safety refusal and language selection...

May 1, 2026 6 min read

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Foresighted Policy Optimization Prevents RLHF Alignment Collapse

arXiv: Perturbation Probing Reveals LLM Behavioral Circuits