Paragraph Boundaries Are Not White Space:Compression Depth as the Signature of Hierarchical Structure

Abstract:Standard positional encodings represent position as a one-dimensional reading-order coordinate, but reading order alone does not determine hierarchical textual structure. We use a hierarchical rotary positional encoding (hRoPE) that represents paragraph, sentence, and token indices as separate channels, hold the token sequence fixed, intervene on the paragraph coordinate p1, and measure cross-paragraph attention with a token-distance-exact estimator. Attention is compressed relative to a token-distance-matched baseline in every corpus, but compression alone is not diagnostic of true structure: an architecturally identical channel with density-matched random labels is compressed too, more shallowly. What distinguishes real structure is the depth of compression, which is greater and corpus-dependent while the control's is not. Comparing eight corpus-only quantities across three constructs (lexical persistence, paragraph length, embedding-based coherence), none fully reproduces the cross-corpus ordering of depth, though embedding-based coherence comes closest. Compression depth, not its location, is the reproducible signature of genuine paragraph structure in our setting.

Computation and Language (cs.CL)

arXiv:2609.23551 [cs.CL]

(or arXiv:2609.23551v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2609.23551 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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