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Translation as a Decision Space: A Multi-Agent Perspective on Low-Resource Dialect Generation

arXiv · AI, language, vision and robotics · article · Sep 3, 2026 · UTC

Neural machine translation (NMT) systems typically produce a single output per input, obscuring the alternative decision trajectories implicitly available within multilingual decoding. This opacity becomes particularly problematic in low-resource dialect settings, where multiple linguistically valid realizations may differ in lexical authenticity, register, and structural stability. We propose reframing translation as a structured decision space explored by autonomous translation agents. Instead of analyzing a single output, we model distinct translation pathways as agents operating over a sha

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