Papers by Artem Cherepanov

1 papers
Steering LLM Reasoning Through Bias-Only Adaptation (2025.emnlp-main)

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Challenge: Compared with LoRA and BitFit, training a single steering vector per layer with reinforcement learning requires orders of magnitude fewer resources and isolates a much smaller, more interpretable parameter set.
Approach: They propose to train a single steering vector per layer with reinforcement learning while freezing all base weights to match the accuracy of fully RL-tuned reasoning models.
Outcome: The proposed approach improves on an 8 billion-parameter model while keeping all base weights fixed.

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