AuthTrace: Diagnosing Evidence Construction in Thematically Dense Single-Author Corpora
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Computer Science > Computation and Language
Title:AuthTrace: Diagnosing Evidence Construction in Thematically Dense Single-Author Corpora
Abstract:Evidence construction systems--chunk retrieval, agent memory, knowledge-graph traversal, and thematic indexing--are evaluated on separate benchmarks with incompatible corpora and metrics, making cross-paradigm diagnosis impossible. We introduce AuthTrace, the first diagnostic benchmark that places all major paradigms on a single corpus and query set by exploiting the dual nature of single-author collections. Built on thematically dense corpora where all texts share style, topic, and vocabulary, AuthTrace provides 2,099 instances with exhaustive gold evidence and a fan-in gradient as the primary diagnostic axis. Comparing eight systems across two QA models, we find that (1) evidence recall--not precision--is the dominant predictor of answer quality (r = 0.96); (2) fan-in exposes paradigm-specific collapse patterns, with flat retrieval degrading 3x faster than structured-evidence systems; and (3) full-context prompting fails uniformly, establishing evidence construction as a necessary capacity beyond raw corpus exposure.
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2605.25382 [cs.CL] |
| (or arXiv:2605.25382v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2605.25382
arXiv-issued DOI via DataCite (pending registration)
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