Text Has Curvature
Karish Grover, Hanqing Zeng, Yinglong Xia, Christos Faloutsos, Geoffrey J. Gordon

TL;DR
This paper demonstrates that text inherently possesses curvature, introduces a method to measure it called Texture, and shows its practical utility in improving language tasks without geometric training.
Contribution
It defines a text-native curvature measure called Texture, provides empirical and theoretical evidence of inherent language curvature, and applies it to enhance language modeling and retrieval tasks.
Findings
Language exhibits inherent non-flat curvature.
Texture effectively measures and defines text curvature.
Curvature-guided methods improve language task performance.
Abstract
Does text have an intrinsic curvature? Language is increasingly modeled in curved geometries - hyperbolic spaces for hierarchy, mixed-curvature manifolds for compositional structure - yet a basic scientific question remains unresolved: what does curvature mean for text itself, in a way that is native to language rather than an artifact of the embedding space we choose? We argue that text does indeed have curvature, and show how to detect it, define it, and use it. To this end, we propose Texture, a text-native, word-level discrete curvature signal, and make three contributions. (a) Existence: We provide empirical and theoretical certificates that semantic inference in natural corpora is non-flat, i.e. language has inherent curvature. (b) Definition: We define Texture by reconciling left- and right-context beliefs around a masked word through a Schrodinger bridge, yielding a curvature…
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Taxonomy
TopicsHandwritten Text Recognition Techniques · 3D Shape Modeling and Analysis · Natural Language Processing Techniques
