@inproceedings{samuelsson-2012-hal,
    title = "{HAL}: Challenging Three Key Aspects of {IBM}-style Statistical Machine Translation",
    author = "Samuelsson, Christer",
    booktitle = "Proceedings of the 10th Conference of the Association for Machine Translation in the Americas: Research Papers",
    month = oct # " 28-" # nov # " 1",
    year = "2012",
    address = "San Diego, California, USA",
    publisher = "Association for Machine Translation in the Americas",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2012.amta-papers.15/",
    abstract = "The IBM schemes use weighted cooccurrence counts to iteratively improve translation and alignment probability estimates. We argue that: 1) these cooccurrence counts should be combined differently to capture word correlation; 2) alignment probabilities adopt predictable distributions; and 3) consequently, no iteration is needed. This applies equally well to word-based and phrase-based approaches. The resulting scheme, dubbed HAL, outperforms the IBM scheme in experiments."
}