---
title: "Inject or Navigate? Token-Efficient Retrieval for LLM Analysis of Transactional Legal Documents — Stuff That Spins"
description: "arXiv:2607.05764v1 Announce Type: new Abstract: Answering questions over a set of transactional legal documents is most simply done by injecting the whole corp…"
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date: "2026-07-08T04:00:00+00:00"
modified: "2026-07-08T06:03:37.101868+00:00"
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# Inject or Navigate? Token-Efficient Retrieval for LLM Analysis of Transactional Legal Documents

**Source:** Unknown  
**Published:** July 8, 2026  
**Original:** https://arxiv.org/abs/2607.05764  

## On this page

- [Overview](#overview)

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

## Overview

arXiv:2607.05764v1 Announce Type: new Abstract: Answering questions over a set of transactional legal documents is most simply done by injecting the whole corpus into the LLM's context window on every query. That baseline maximises retrieval recall, but its token footprint scales with the corpus rather than the question, and long-context degradation scales with it. We report what it took to replace full-corpus injection in a legal-document analysis system, comparing it against two structured ret

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