---
title: "SearchEyes: Towards Frontier Multimodal Deep Search Intelligence via Search World Simulation — Stuff That Spins"
description: "arXiv:2607.05943v1 Announce Type: new Abstract: Training multimodal search agents to perform multi-hop reasoning remains challenging due to a fundamental struc…"
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keywords: ["narrative intelligence", "SpinGraph", "AI recall"]
date: "2026-07-08T04:00:00+00:00"
modified: "2026-07-08T06:02:36.523874+00:00"
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# SearchEyes: Towards Frontier Multimodal Deep Search Intelligence via Search World Simulation

**Source:** Unknown  
**Published:** July 8, 2026  
**Original:** https://arxiv.org/abs/2607.05943  

## On this page

- [Overview](#overview)

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

## Overview

arXiv:2607.05943v1 Announce Type: new Abstract: Training multimodal search agents to perform multi-hop reasoning remains challenging due to a fundamental structural disconnect: existing pipelines construct training data, search environments, and reward signals independently, causing synthesized structural metadata to be discarded, environments to rely on irreproducible external engines, and RL rewards to remain sparse at the trajectory level. We present \textbf{SearchEyes}, which uses a typed kn

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