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 g
The proliferation of various AI agent and evidence construction systems necessitates a unified evaluation framework to improve their diagnostic capabilities and comparability.
This benchmark addresses a critical gap in AI evaluation, enabling more robust and comparable assessment of agentic systems, which are central to collapsing workflows.
Previously disparate evaluation paradigms for evidence construction can now be directly compared and diagnosed on a single, thematically dense corpus.
- · AI model developers
- · AI research institutions
- · Companies deploying AI agents
- · End-users of AI agent systems
- · Fragmented AI evaluation methodologies
- · Systems with poor diagnostic capabilities
Improved performance and reliability of AI evidence construction systems.
Accelerated development and adoption of more capable and trustworthy AI agents across various industries.
Enhanced competition among AI developers leading to more sophisticated agentic AI capabilities and a faster collapse of white-collar workflows.
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Read at arXiv cs.CL