Barenholtz 自生成语言理论如何补充 Harris 的整合主义语言学
How Do I Know What to Say Next? Barenholtz's Autogenerative Theory as an Enrichment of Harrisean Integrationism
AI 导读
这篇哲学论文论证 Elan Barenholtz 基于 LLM 行为提出的语言自生成理论，可以弥补 Roy Harris 整合主义语言学的三个解释缺口。自生成理论为 Harris 所强调的双向沟通的前瞻开放性提供结构机制，为语言与其他符号活动的符号连续性论题给出计算对应物，并提出关于历史整合积累档案的理论。
正文 · 原文
Abstract:Roy Harris's Integrationist linguistics offers a compelling critique of the referentialist tradition embedded deep at the heart of computational approaches to language, arguing that language is not a code that maps onto a pre-given world but a situated, bipartite activity oriented toward prospective joint action. Yet Integrationism leaves certain explanatory gaps: it does not fully account for the structural mechanism by which signs sustain prospective openness, it undertheorises the continuity between linguistic and non-linguistic semiotic activity, and it offers no detailed account of the structural properties of the accumulated archive of past integrations. This paper argues that Elan Barenholtz's autogenerative theory of language, developed in response to the behaviour of Large Language Models (LLMs), can fill precisely these gaps, enriching Integrationism without undermining any of its core commitments. Specifically, the autogenerative account provides: a structural mechanism for the prospective openness that Harris identifies as central to bipartite communication; a computational correlate for Harris's thesis of semiotic continuity between language and other sign-making activity; and a theory of the archive: what the accumulated residue of past integrations looks like and how new participants draw upon it. The synthesis preserves Harris's ontological primacy of the situated integrative act while adding explanatory content that Integrationism itself does not supply. For practitioners and researchers in natural language processing and large language model design, the argument offers a principled account of what the statistical structure that LLMs so effectively exploit actually is, and of what it cannot, by its nature, provide.
| Comments: | Submitted to Philosophy and Technology |
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2607.07891 [cs.CL] |
| (or arXiv:2607.07891v2 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2607.07891 arXiv-issued DOI via DataCite |
Submission history
From: John Bishop Prof [view email]
[v1]
Wed, 8 Jul 2026 19:54:18 UTC (14 KB)
[v2]
Fri, 23 Oct 2026 16:15:31 UTC (14 KB)
来源：arXiv cs.AI · arxiv.org