# SHARE：面向研究与教育的社会科学与人文 AI

- 来源：HuggingFace Daily Papers（社区热门论文）
- 发布时间：2026-04-13 08:00
- AIHOT 链接：https://aihot.virxact.com/items/cmnyiu21900c4sl13998p3ex9
- 原文链接：https://arxiv.org/abs/2604.11152

## AI 摘要

SHARE 系列是首个专为社会科学与人文学科（SSH）全量预训练的因果语言模型，在 SSH Cloze 基准测试中，其文本建模性能接近使用 100 倍 token 的通用模型 Phi-4。同期发布的 MIRROR 用户界面采用零文本生成设计，支持 SSH 学者批判性审阅文本输入，在不违背学科原则与规范的前提下释放 AI 能力。

## 正文

This intermediate technical report introduces the SHARE family of base models and the MIRROR user interface. The SHARE models are the first causal language models fully pretrained by and for the social sciences and humanities (SSH). Their performance in modelling SSH texts is close to that of general purpose models (Phi-4) which use 100 times more tokens, as shown by our custom SSH Cloze benchmark. The MIRROR user interface is designed for reviewing text inputs from the SSH disciplines while preserving critical engagement. By prototyping a generative AI interface that does not generate any text, we propose a way to harness the capabilities of the SHARE models without compromising the integrity of SSH principles and norms.