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cs.CL2026
Improving Term Evaluation in Machine Translation: Variation Matters
Nicolas Dahan, Ziqian Peng, François Yvon +1
Terminology evaluation in machine translation (MT) usually assumes a single correct target form per source term. However, human translators routinely introduce variation that curre…
cs.CL2025
Quantifying Conversation Drift in MCP via Latent Polytope
Haoran Shi, Hongwei Yao, Shuo Shao +4
The Model Context Protocol (MCP) enhances large language models (LLMs) by integrating external tools, enabling dynamic aggregation of real-time data to improve task execution. Howe…
cs.CL2024
Investigating Length Issues in Document-level Machine Translation
Ziqian Peng, Rachel Bawden, François Yvon
Transformer architectures are increasingly effective at processing and generating very long chunks of texts, opening new perspectives for document-level machine translation (MT). I…