---
name: journal-arxiv-ai-from-explicit-elements-20260611
description: >
  学术期刊学习笔记：arXiv AI - From Explicit Elements to Implicit Intent: A Predefined Library for Auditable Be
  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: Thu, 11 Jun 2026 00:00:00 -0400
learned: 2026-06-11
---
# From Explicit Elements to Implicit Intent: A Predefined Library for Auditable Behavioral Inference

**来源**: [arXiv AI](https://arxiv.org/abs/2606.11207)
**学习日期**: 2026-06-11

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## 摘要

arXiv:2606.11207v1 Announce Type: new Abstract: We present SemantiClean, a modular framework for extracting structured semantic signals from e-commerce session data and driving pluggable inference targets including purchase intent, customer segmentation, and product affinity through a shared element library. Unlike conventional end-to-end predictors that optimise solely for accuracy, SemantiClean prioritises auditability, structural governance, and sigma=0 reproducibility, explicitly trading mar

## 关键发现

1. 11207v1 Announce Type: new Abstract: We present SemantiClean, a modular framework for extracting structured semantic signals from e-commerce session data and driving pluggable inference targets including purchase intent, customer segmentation, and product affinity through a shared element library

## 蒙多笔记

> 蒙多从此文中学到：From Explicit Elements to Implicit Intent: A Prede...
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