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Researcher profile

Alexandra Birch

10 papers in the PaperMetrix corpus

Publications

Papers by this author

  1. Survey of Low-Resource Machine Translation

    2021 · arXiv (Cornell University)

    We present a survey covering the state of the art in low-resource machine translation research. There are currently around 7000 languages spoken in the world and almost all language pairs lack significant resources for training …

  2. Code-Switching with Word Senses for Pretraining in Neural Machine Translation

    2023 · arXiv (Cornell University)

    Lexical ambiguity is a significant and pervasive challenge in Neural Machine Translation (NMT), with many state-of-the-art (SOTA) NMT systems struggling to handle polysemous words (Campolungo et al., 2022). The same holds for the NMT pretraining …

  3. ExpertSteer: Intervening in LLMs through Expert Knowledge

    2025 · arXiv (Cornell University)

    Large Language Models (LLMs) exhibit remarkable capabilities across various tasks, yet guiding them to follow desired behaviours during inference remains a significant challenge. Activation steering offers a promising method to control the generation process of …

  4. Neural Machine Translation of Rare Words with Subword Units

    2016

    Neural machine translation (NMT) models typically operate with a fixed vocabulary, but translation is an open-vocabulary problem. Previous work addresses the translation of out-of-vocabulary words by backing off to a dictionary. In this paper, we …

  5. Controlling Politeness in Neural Machine Translation via Side Constraints

    2016

    Many languages use honorifics to express politeness, social distance, or the relative social status between the speaker and their addressee(s). In machine translation from a language without honorifics such as English, it is difficult to …

  6. Nematus: a Toolkit for Neural Machine Translation

    2017

    Rico Sennrich, Orhan Firat, Kyunghyun Cho, Alexandra Birch, Barry Haddow, Julian Hitschler, Marcin Junczys-Dowmunt, Samuel Läubli, Antonio Valerio Miceli Barone, Jozef Mokry, Maria Nădejde. Proceedings of the Software Demonstrations of the 15th Conference of the …

  7. Predicting Target Language CCG Supertags Improves Neural Machine Translation

    2017

    Neural machine translation (NMT) models are able to partially learn syntactic information from sequential lexical information. Still, some complex syntactic phenomena such as prepositional phrase attachment are poorly modeled. This work aims to answer two …

  8. The University of Edinburgh's Neural MT Systems for WMT17

    2017

    Rico Sennrich, Alexandra Birch, Anna Currey, Ulrich Germann, Barry Haddow, Kenneth Heafield, Antonio Valerio Miceli Barone, Philip Williams. Proceedings of the Second Conference on Machine Translation. 2017.

  9. Evaluating Discourse Phenomena in Neural Machine Translation

    2018

    Rachel Bawden, Rico Sennrich, Alexandra Birch, Barry Haddow. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers). 2018.

  10. Evaluating Discourse Phenomena in Neural Machine Translation

    2017 · Zurich Open Repository and Archive (University of Zurich)

    For machine translation to tackle discourse phenomena, models must have access to extra-sentential linguistic context. There has been recent interest in modelling context in neural machine translation (NMT), but models have been principally evaluated with …