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Parsa Razmara

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#artificial intelligence Preprint Oct 2026

The Sharp Directions Are Against You: Curvature Analysis of Activation Steering

Activation steering adds a vector to a language model's internal representations at inference time. It is a lightweight alternative to fine-tuning for behavioral control. The standard construction, contrastive activation addition (CAA), is fragile, as on many inputs it shifts behavior in the wrong direction. To explain...

Seyedarmin Azizi, Arya Fayyazi, Parsa Razmara et al. · 0 citations
#machine learning Review Sep 2026

Best Practices in EEG Analysis: Preprocessing, Modeling, and Machine Learning

Electroencephalography (EEG) analysis requires careful choices in preprocessing, statistical modeling, and machine learning because EEG signals are highly susceptible to artifacts, volume conduction, low signal-to-noise ratio, and substantial inter-subject variability. This chapter provides a practical and methodologic...

Parsa Razmara, Woojae Jeong, Aditya Kommineni et al. · 0 citations
Preprint Aug 2026

CircuitSteer: Geometrically Aligned Multi-Layer Steering via Sparse Autoencoder Circuits

CircuitSteer is introduced, a novel framework that leverages Sparse Autoencoders (SAEs) to identify and manipulate coherent semantic circuits distributed across multiple layers that yields strictly more robust and effective behavioral control than static single-point interventions.

Mehrshad Saadatinia, Parsa Razmara, Ardalan Aryashad et al. · 1 citation

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