Text Corpora as Concept Fields: Providing Explainable Groundedness
Read the original on arXiv Computation and Language →The paper introduces the Concept Field, a local drift field with pointwise uncertainty derived from sentence-embedding deltas in a text corpus. It scores candidate sentence transitions using the mean absolute z-distance (ζ) to quantify groundedness, offering a model‑agnostic, corpus‑attributable metric. The authors implement a Vector Sequence Database to store embeddings and delta metadata, and demonstrate the method’s effectiveness in detecting groundedness in the U.S. Code of Federal Regulations and novelty in Project Gutenberg, achieving strong selective classification performance under a triage policy.
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