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cs.CL2026
Rubric-as-Experts: Case-Specific MQM Rubrics for Translation Quality Evaluation
Weilu Xu, Yunzhi Shen, Xinye Wang +2
Large language models (LLMs) have shown strong potential in fine-grained translation quality evaluation (QE), yet existing MQM-based approaches typically rely on fixed rubric confi…
cs.CL2026
Unlocking Fine-Grained Translation Quality Estimation in LRMs through Mutually Boosting Implicit and Explicit Reasoning
Renfei Dang, Xinye Wang, Zhejian Lai +5
Large Reasoning Models (LRMs) still struggle with fine-grained translation quality estimation (QE), even with long reasoning chains. We argue that LRMs already possess strong multi…
cs.CL2026
Probing Ethical Framework Representations in Large Language Models: Structure, Entanglement, and Methodological Challenges
Weilun Xu, Alexander Rusnak, Frederic Kaplan
When large language models make ethical judgments, do their internal representations distinguish between normative frameworks, or collapse ethics into a single acceptability dimens…