@inproceedings{ostermann-etal-2026-weights,
title = "From Weights to Activations: Is Steering the Next Frontier of Adaptation?",
author = "Ostermann, Simon and
Gurgurov, Daniil and
Baeumel, Tanja and
Hedderich, Michael A. and
Lapuschkin, Sebastian and
Samek, Wojciech and
Schmitt, Vera",
editor = "Liakata, Maria and
Moreira, Viviane P. and
Zhang, Jiajun and
Jurgens, David",
booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
month = jul,
year = "2026",
address = "San Diego, California, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.acl-long.1377/",
pages = "29854--29879",
ISBN = "979-8-89176-390-6",
abstract = "Post-training adaptation of large language models is commonly achieved through parameter updates or input based methods such as fine-tuning, parameter-efficient adaptation, and prompting. In parallel, a growing body of work modifies internal activations at inference time to influence model behavior, an approach known as *steering*. Despite increasing use, steering is rarely analyzed within the same conceptual framework as established adaptation methods.In this work, we argue that steering should be regarded as a form of model adaptation. We introduce a set of functional criteria for adaptation methods and use them to compare steering approaches with classical alternatives. This analysis positions steering as a distinct adaptation paradigm based on targeted interventions in activation space, enabling local and reversible behavioral change without parameter updates. The resulting framing clarifies how steering relates to existing methods, motivating a unified taxonomy for model adaptation."
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%0 Conference Proceedings
%T From Weights to Activations: Is Steering the Next Frontier of Adaptation?
%A Ostermann, Simon
%A Gurgurov, Daniil
%A Baeumel, Tanja
%A Hedderich, Michael A.
%A Lapuschkin, Sebastian
%A Samek, Wojciech
%A Schmitt, Vera
%Y Liakata, Maria
%Y Moreira, Viviane P.
%Y Zhang, Jiajun
%Y Jurgens, David
%S Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, United States
%@ 979-8-89176-390-6
%F ostermann-etal-2026-weights
%X Post-training adaptation of large language models is commonly achieved through parameter updates or input based methods such as fine-tuning, parameter-efficient adaptation, and prompting. In parallel, a growing body of work modifies internal activations at inference time to influence model behavior, an approach known as *steering*. Despite increasing use, steering is rarely analyzed within the same conceptual framework as established adaptation methods.In this work, we argue that steering should be regarded as a form of model adaptation. We introduce a set of functional criteria for adaptation methods and use them to compare steering approaches with classical alternatives. This analysis positions steering as a distinct adaptation paradigm based on targeted interventions in activation space, enabling local and reversible behavioral change without parameter updates. The resulting framing clarifies how steering relates to existing methods, motivating a unified taxonomy for model adaptation.
%U https://aclanthology.org/2026.acl-long.1377/
%P 29854-29879
Markdown (Informal)
[From Weights to Activations: Is Steering the Next Frontier of Adaptation?](https://aclanthology.org/2026.acl-long.1377/) (Ostermann et al., ACL 2026)
ACL
- Simon Ostermann, Daniil Gurgurov, Tanja Baeumel, Michael A. Hedderich, Sebastian Lapuschkin, Wojciech Samek, and Vera Schmitt. 2026. From Weights to Activations: Is Steering the Next Frontier of Adaptation?. In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 29854–29879, San Diego, California, United States. Association for Computational Linguistics.