Agent Eng News Wednesday, October 28, 2026 · Today’s edition · 3 stories
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The HoS abstract reports that learned per-head attention gates reduced RL-Hammer attack success against GPT-OSS-20B from 97% to 10%.
Why it matters: For agent builders, the abstract suggests attention-level instruction-data separation may improve robustness without the reported utility losses seen in some alternatives under few-shot prompting. Its results cover two models and specified attack and benchmark settings, so they do not establish performance beyond those evaluations.
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