XDomainBench: Diagnosing Reasoning Collapse in High-Dimensional Scientific Knowledge Composition

• URL: http://arxiv.org/abs/2605.14754v1
• Date: Thu, 14 May 2026 12:19:19 GMT
• Title: XDomainBench: Diagnosing Reasoning Collapse in High-Dimensional Scientific Knowledge Composition
• Abstract summary: XDomainBench is a diagnostic benchmark for interactive interdisciplinary scientific reasoning.<n>We formalize the composition order and mixture structure to enable systematic stress-testing from single-discipline to inter-disciplinary.<n>Large-scale evaluation of LLMs reveals a systematic reasoning collapse as composition order increases.
• Score: 55.07589952126153
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Large Language Models (LLMs) are increasingly deployed for knowledge synthesis, yet their capacity for compositional generalization in scientific knowledge remains under-characterized. Existing benchmarks primarily focus on single-turn restricted scenarios, failing to capture the capability boundaries exposed by real-world interactive scientific workflows. To address this, we introduce XDomainBench, a diagnostic benchmark for interactive interdisciplinary scientific reasoning. We formalize the composition order and mixture structure to enable systematic stress-testing from single-discipline to inter-disciplinary, comprising 8,598 interactive sessions across 20 domains and 4 task categories, with 8 realistic trajectory patterns covering difficulty and domain-mixture dynamics, simulating real AI4S scenarios. Large-scale evaluation of LLMs reveals a systematic reasoning collapse as composition order increases, stemming from two root causes: (i) direct difficulty increases induced by domain composition, and (ii) indirect interaction-amplified failures where trajectory patterns trigger error accumulation, reasoning breaks, and domain confusion, ultimately leading to session collapse.

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