#InstaBoost
Excited to share our new paper: "Instruction Following by Boosting Attention of Large Language Models"!

We introduce Instruction Attention Boosting (InstABoost), a simple yet powerful method to steer LLM behavior by making them pay more attention to instructions.
(🧵1/7)
July 10, 2025 at 6:22 PM
LLM ignoring instructions? Make it listen with InstABoost.

✅ Simple: Steer your model in 5 lines of code

✅ Effective: Outperforms latent steering & prompt-only methods

✅ Grounded: Based on our mechanistic theory on rule-following (LogicBreaks)

Blog: debugml.github.io/instaboost
July 10, 2025 at 6:46 PM
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August 27, 2025 at 8:42 PM
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January 23, 2025 at 1:52 AM
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December 15, 2025 at 10:59 PM
December 7, 2024 at 5:36 AM
Crucially, InstABoost achieves this control without degrading text quality. While other latent steering methods can cause generation fluency to drop sharply as you increase their strength, InstABoost maintains coherence while steering towards the instruction.
(6/7)
July 10, 2025 at 6:22 PM
Across 15 tasks, InstABoost either outperforms or matches the best steering method (prompt or latent-based). For tasks where prompt and latent-based steering perform equivalently, InstABoost can even combine the strengths of both and outperform both categories of methods.
(5/7)
July 10, 2025 at 6:22 PM
InstABoost steers an LLM in attention space, bridging the performance gap between latent and prompt-based steering. InstABoost can be implemented in ~3 lines of code which simply increases attention weight to an in-context instruction.
(3/7)
July 10, 2025 at 6:22 PM
@rohanpaul_ai https://x.com/rohanpaul_ai/status/1935876505701101632 #x-rohanpaul_ai

Controlling LLM generation reliably for safety remains a central challenge.

This paper introduces Instruction Attention Boosting, INSTABOOST.

It boosts instruction prompting strength by altering att...
June 20, 2025 at 2:00 AM
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February 21, 2025 at 1:58 PM
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February 21, 2025 at 1:40 PM
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February 21, 2025 at 12:43 PM