FLAS learns a multi-step velocity field v_t(h,t,c) to steer activations, outperforming prompting with harmonic means of 1.015 and 1.113 on two Gemma models without per-concept tuning.
Caught in the act: a mechanistic approach to detecting deception
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CL 2years
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UNVERDICTED 2representative citing papers
Deception probes in LLMs collapse under stylistic shifts but recover with style-augmented training, rejecting single-direction and entropy hypotheses in favor of distributed multi-dimensional signals.
citing papers explorer
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Beyond Steering Vector: Flow-based Activation Steering for Inference-Time Intervention
FLAS learns a multi-step velocity field v_t(h,t,c) to steer activations, outperforming prompting with harmonic means of 1.015 and 1.113 on two Gemma models without per-concept tuning.
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Pressure-Testing Deception Probes in LLMs: Scaling, Robustness, and the Geometry of Deceptive Representations
Deception probes in LLMs collapse under stylistic shifts but recover with style-augmented training, rejecting single-direction and entropy hypotheses in favor of distributed multi-dimensional signals.