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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2604.11152 |
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| _version_ | 1866915934593089536 |
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| author | Gonçalves, João de Jager, Sonia Knoth, Petr Pride, David Jelicic, Nick |
| author_facet | Gonçalves, João de Jager, Sonia Knoth, Petr Pride, David Jelicic, Nick |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_11152 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | SHARE: Social-Humanities AI for Research and Education Gonçalves, João de Jager, Sonia Knoth, Petr Pride, David Jelicic, Nick Computation and Language 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. |
| title | SHARE: Social-Humanities AI for Research and Education |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2604.11152 |