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ReviseMate: Exploring Contextual Support for Digesting STEM Paper Reviews
Yuansong Xu, Shuhao Zhang, Yijie Fan, Shaohan Shi, Zhenhui Peng, Quan Li
https://arxiv.org/abs/2508.15148

ReviseMate: Exploring Contextual Support for Digesting STEM Paper Reviews
Effectively assimilating and integrating reviewer feedback is crucial for researchers seeking to refine their papers and handle potential rebuttal phases in academic venues. However, traditional review digestion processes present challenges such as time consumption, reading fatigue, and the requisite for comprehensive analytical skills. Prior research on review analysis often provides theoretical guidance with limited targeted support. Additionally, general text comprehension tools overlook the…

Animer une base de connaissance: des ontologies aux mod{\`e}les d'I.A. g{\'e}n{\'e}rative
Peter Stockinger (ESCOM, PLIDAM, Inalco, CIS)
https://arxiv.org/abs/2509.01304

Animer une base de connaissance: des ontologies aux mod{è}les d'I.A. g{é}n{é}rative
In a context where the social sciences and humanities are experimenting with non-anthropocentric analytical frames, this article proposes a semiotic (structural) reading of the hybridization between symbolic AI and neural (or sub-symbolic) AI based on a field of application: the design and use of a knowledge base for area studies. We describe the LaCAS ecosystem -- Open Archives in Linguistic and Cultural Studies (thesaurus; RDF/OWL ontology; LOD services; harvesting; expertise; publication), d…