AuthTrace: Diagnosing Evidence Construction in Thematically Dense Single-Author Corpora 文章

ArXiv CS.CL2026-05-26NEWSen作者: Xiaoqing Wu, Feifei Li, Haoliang Ming, Wenhui Que

摘要

arXiv:2605.25382v1 Announce Type: new 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;