Speaking the Language of Science: Toward a General-Purpose Generative Foundation Model for the Natural Sciences 文章

ArXiv CS.CL2026-06-16NEWSen作者: Mingyang Li, Yurou Liu, Jieping Ye, Bing Su, Ji-Rong Wen, Zheng Wang

详细信息

来源站点
ArXiv CS.CL
作者
Mingyang Li, Yurou Liu, Jieping Ye, Bing Su, Ji-Rong Wen, Zheng Wang
文章类型
NEWS
语言
en
发布日期
2026-06-16

摘要

arXiv:2606.16905v1 Announce Type: new Abstract: In this report, we present LOGOS (Language Of Generative Objects in Science), a scientific generative language model that unifies heterogeneous tasks across the natural sciences within a single autoregressive framework based on a shared scientific grammar. It encodes diverse scientific objects and their spatial interactions as token sequences over a common vocabulary. By representing spatial contact and constraint patterns as discrete tokens, the model captures complex structural interactions in a purely sequential manner, without relying on explicit coordinates or geometric neural networks. This unified representation enables a wide range of downstream tasks to be formulated consistently as next-token prediction in the same grammar space, creating strong alignment between continued multi-domain pre-training and downstream objectives.

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