Author

O. Hofman

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Preprint Sep 2026

BadEngram: Backdoor Attack on Gated Memory Components in LLMs

To expand open-weight models'capacity without proportionally increasing computation, recent architectures incorporate gated parametric memory that retrieves learned values and injects them into intermediate representations. One representative design is Engram, which combines deterministic n-gram lookup with context-dep...

Ariel Fogel, O. Hofman, E. Cohen et al. · 0 citations

#machine learning Dec 2025

Training-Free Policy Violation Detection via Activation-Space Whitening in LLMs

This work proposes a training-free method that operates directly on the LLM internal representations, leveraging prior evidence that decision-relevant information is encoded within them, and derives policy-violation scores directly from normalized representations of LLM hidden activations.

Oren Rachmil, Roy Betser, Itay Gershon et al. · arXiv.org · 5 citations · ⚡1

Preprint Aug 2026

An Actionable Diagnosis of Multilingual, Multi-Agent Planning Failures

To test whether the taxonomy supports mitigation, TART, Taxonomy-Guided Actionable Representation, is introduced that makes the taxonomy's key aspects explicit to the planner and downstream sub-agents and consistently improves performance.

Vikas Pahuja, J. Brokman, O. Hofman et al. · 0 citations