arXiv AI By Arthur Wuhrmann, Gaetan Stein, Daniel Brunner, Andrei Kucharavy

Measuring & Mitigating Over-Alignment for LLMs in Multilingual Criminal Law Courts

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arXiv:2606. 23375v2 Announce Type: replace-cross Abstract: While the wider applicability of LLMs in the legal field is currently debated due to their reliability and the gravity of any errors, narrow uses with well-understood and mitigated risks have emerged.

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arXiv AI
Jun 18

TW-LegalBench: Measuring Taiwanese Legal Understanding

arXiv:2606. 18699v1 Announce Type: cross Abstract: Large language models (LLMs) have shown impressive capabilities across diverse tasks, yet their performance on jurisdiction-specific legal reasoning remains underexplored.

By Fei-Yueh Chen, Chun Huang Lin, Chan Wei Hsu, Kuan Hsuan Yeh, Zih-Ching Chen, Kuan-Ming Chen, Patrick Chung-Chia Huang
arXiv Computation and Language
Sep 24

Cross-Lingual Legal QA for Vietnamese Labour Law: Retrieval, Translation, and Verifier-Guided Correction

The paper presents a cross‑lingual legal QA system for Vietnamese labour law, introducing a bilingual evaluation suite of 231 Vietnamese–English question–answer pairs, 75 of which are annotated for five complex legal reasoning phenomena. It evaluates a verifier‑guided pipeline that decomposes answers into claims, checks citation reachability and entailment, and corrects citation failures and contradictions, and introduces six automatic diagnostics for faithfulness to retrieved evidence. Experiments show that dense retrieval outperforms sparse and hybrid retrieval, translation placement has no significant effect on diagnostics, and verifier‑guided correction modestly improves citation preservation but not other dimensions, with human evaluation indicating a gap between automatic diagnostics and human judgments.

By Nguyen Minh Chi, Mo El-Haj, Nguyen Ha Thanh, Dawn Knight, Paul Rayson