arXiv:2607. 19856v1 Announce Type: cross Abstract: FinMMEval 2026 Task 1 evaluates multilingual financial multiple-choice question answering in English, Chinese, Arabic, and Hindi.
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arXiv:2607. 19867v1 Announce Type: cross Abstract: FinMMEval 2026 Task 2 evaluates short-answer financial question answering over multilingual evidence.
arXiv:2607. 22841v1 Announce Type: cross Abstract: We present DS@GT's submission to FinMMEval 2026 Task 1, a multilingual financial exam question answering benchmark spanning English, Spanish, Greek, Chinese, and Hindi.
arXiv:2606. 07167v1 Announce Type: cross Abstract: Meaningful multilingual evaluation must test models in the target language and educational context.
arXiv:2608. 04374v1 Announce Type: cross Abstract: Large language models can produce fluent financial analysis, but fluency alone does not establish whether a report is suitable for institutional delivery.
arXiv:2604. 04532v2 Announce Type: replace-cross Abstract: Evaluation language is typically treated as a fixed English default in agentic code benchmarks, yet we show that changing the judge's language can invert backbone rankings.
arXiv:2608. 08634v1 Announce Type: new Abstract: Open-weight language models from Chinese AI labs caught up on benchmarks relative to proprietary frontier models in recent months.