mlsanityData to 7 Oct 2026

Precise Attribute Intensity Control in Large Language Models via Targeted Representation Editing

arXiv 2510.12121 ↗First posted 14 Oct 2025cs.AI cs.CL cs.LGcited by 2

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Abstract (arXiv)

Precise attribute intensity control--generating Large Language Model (LLM) outputs with specific, user-defined attribute intensities--is crucial for AI systems adaptable to diverse user expectations. Current LLM alignment methods, however, typically provide only directional or open-ended guidance, failing to reliably achieve exact attribute intensities. We address this limitation with three key designs: (1) reformulating precise attribute intensity control as a target-reaching problem, rather than simple maximization; (2) training a lightweight value function via temporal-difference learning to predict final attribute intensity scores from partial generations, thereby steering LLM outputs; and (3) employing gradient-based interventions on hidden representations to navigate the model precisely towards specific attribute intensity targets. Our method enables fine-grained, continuous control over attribute intensities, moving beyond simple directional alignment. Experiments on LLaMA-3.2-3b and Phi-4-mini confirm our method's ability to steer text generation to user-specified attribute intensities with high accuracy. Finally, we demonstrate efficiency enhancements across three downstream tasks: preference data synthesis, Pareto frontier approximation and optimization, and distillation of aligned behaviors for intervention-free inference. Our code is available on https://github.com/Pre-Control/pre-control

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 47 of its 52 references that are in the map. First posted on arXiv 14 Oct 2025.

Builds on

47 of 52 references.

References · 47

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35 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026Enabling Performant and Flexible Model-Internal Observability for LLM Inferencecited by 0
  2. 2026Persona Dosing: Calibrated Activation Steering for Graded Trait Controlcited by 0

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