Papers with path selection

2 papers
Unsupervised Pivot Translation for Distant Languages (P19-1)

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Challenge: Unsupervised neural machine translation (NMT) is a popular method for transferring information between languages.
Approach: They propose an unsupervised pivot translation method which translates a language to a distant language through multiple hops.
Outcome: The proposed method improves translation on 20 languages and 294 distant languages on 20 different languages and language pairs.
Martingale Foresight Sampling: A Principled Approach to Inference-Time LLM Decoding (2026.eacl-long)

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Challenge: Standard autoregressive decoding in large language models is short-sighted, often failing to find globally optimal reasoning paths due to token-by-token generation process.
Approach: They propose a principled framework that reformulates LLM decoding as a problem of identifying an optimal stochastic process.
Outcome: The proposed framework surpasses state-of-the-art methods in accuracy while significantly improving computational efficiency.

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