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title: "Safe Inference-Time Alignment via Lagrangian Reward Augmentation — Stuff That Spins"
description: "arXiv:2607.02781v1 Announce Type: new Abstract: Inference-time alignment steers a frozen language model during decoding using auxiliary reward signals, avoidin…"
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date: "2026-07-07T04:00:00+00:00"
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# Safe Inference-Time Alignment via Lagrangian Reward Augmentation

**Source:** Unknown  
**Published:** July 7, 2026  
**Original:** https://arxiv.org/abs/2607.02781  

## On this page

- [Overview](#overview)

<a id="overview"></a>

## Overview

arXiv:2607.02781v1 Announce Type: new Abstract: Inference-time alignment steers a frozen language model during decoding using auxiliary reward signals, avoiding the cost of repeated weight updates. However, existing inference-time alignment methods typically optimize a single scalar score, so explicit safety constraints must either be ignored or encoded through manually tuned penalties. We propose Lagrangian Reward Augmentation (LARA), a general inference-time alignment framework under safety co

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