Author

Gil Ben-Artzi

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Preprint Aug 2026

Circuit Fine-Tuning for Compute-Efficient Transformer Adaptation

Circuit Fine-Tuning is introduced, a compute-efficient framework that uses circuit discovery---conventionally used to explain trained models---to select modules for fine-tuning before training to isolate the response of the backbone to the target distribution rather than the preferences of a particular classifier.

Uri Z. Kialy, Gil Ben-Artzi · 0 citations

#small language model Preprint Aug 2026

Mixture of Channel Experts: Static Sparse Supports with Input-Adaptive Mixing for Pointwise Projections

This work introduces Mixture of Channel Experts (MoCE), a structured sparse channel-mixing layer, inspired by MoE, that replaces pointwise (1x1) channel-reduction projections and matches or exceeds dense baselines and prior channel-selection methods while reducing MACs by 16.7% and end-to-end latency.

Elian Iluk, Gil Ben-Artzi · 0 citations