PatTransBench: an ipc-stratified, multi-dimensional benchmark for patent machine translation evaluation

Abstract:We present PatTransBench, a 12,000-item Chinese-English/Japanese/Korean patent machine translation (PatMT) benchmark with a four-dimensional evaluation protocol. The benchmark comprises 6,000 short-text (sentence/claim) and 6,000 long-text (paragraph) pairs, evenly split across three language pairs and both translation directions, built via IPC-section-stratified sampling and dualthreshold quality gating from upstream patent-family parallel corpora. The evaluation protocol spans literal n-gram overlap (BLEU, ROUGE-L, chrF), cross-lingual semantic textual similarity (CLSTS), 38-probe-language consistency testing, and serving performance under concurrency. A case study on PatMT2-7B and its fp8/AWQ4/AutoRound-4bit variants reveals direction-dependent quantization effects masked by aggregate scores and non-monotonic language-failure patterns across quantization schemes that are invisible to single-metric evaluation. We plan to release the benchmark, protocol, and case-study results upon publication to support reproducible PatMT evaluation.

Computation and Language (cs.CL); Artificial Intelligence (cs.AI)

arXiv:2610.16538 [cs.CL]

(or arXiv:2610.16538v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2610.16538 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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