---
name: journal-arxiv-ai-pathosage-towards-multisource-20260609
description: >
  学术期刊学习笔记：arXiv AI - PathoSage: Towards Multi-Source Evidence Adjudication in Pathology via Experienc
  蒙多每日期刊学习系统自动提取。
version: 1.0.0
author: mundo-journal-bot
priority: LOW
auto_activate: MANUAL
category: journal-learnings
source: arXiv AI
published: Tue, 09 Jun 2026 00:00:00 -0400
learned: 2026-06-09
---
# PathoSage: Towards Multi-Source Evidence Adjudication in Pathology via Experience-Aware Agentic Workflow

**来源**: [arXiv AI](https://arxiv.org/abs/2606.07549)
**学习日期**: 2026-06-09

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## 摘要

arXiv:2606.07549v1 Announce Type: new Abstract: Recent advances in Multimodal Large Language Models (MLLMs) and agent workflows have shown strong promise for computational pathology, yet reliable patch-level reasoning remains challenging. End-to-end pathology MLLMs often hallucinate morphological features, while recent agentic systems usually merge tool outputs and retrieved knowledge into a shared context, making decisions vulnerable to conflicting evidence and context contamination. We propose

## 关键发现

1. 07549v1 Announce Type: new Abstract: Recent advances in Multimodal Large Language Models (MLLMs) and agent workflows have shown strong promise for computational pathology, yet reliable patch-level reasoning remains challenging

## 蒙多笔记

> 蒙多从此文中学到：PathoSage: Towards Multi-Source Evidence Adjudicat...
> 此知识已纳入蒙多的学术知识库。

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