2026
Makoto Takenaka, Hitomi Yanaka
· International Conference on... · 0 citations
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This work introduces a reliable evaluation approach for DDG, based on newly proposed evaluation criteria and powered by an LLM-as-a-judge, and proposes an LLM-based LDDG approach that employs iterative simplification.
Yusuke Ide, Adam Nohejl, Joshua Tanner et al.
· arXiv.org · 2 citations
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Experimental results show that FRC-based fine-tuning substantially improves 7B LLMs over direct Doc2Doc fine-tuning and outperforms existing DocMT methods on IWSLT2017.
Xiao-Tian Wang, You-Yuan Lin, Zhan Shen et al.
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This work proposes CAROT (Cross-Lingual Alignment of Representations in a Language-Agnostic Space via Optimal Transport), which consists of identifying language-specific representations in LLMs'internal states and aligning language-agnostic representations across languages at the token level by optimal transport, while...
Taisei Yamamoto, Ryoma Kumon, Danushka Bollegala et al.
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Jul 2026
The results empirically show that relation geometry is not equally well-represented for all relations in semantic space, suggesting that there is a difference in how well semantic relations might be learned from distributional information alone.
Zhihan Cao, Hiroaki Yamada, Simone Teufel et al.
· arXiv.org · 0 citations
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