minimalparts/nonce2vec

Fixed bug on empty probs in informativeness

This is the version accompanying the SRW 2019 paper *Towards Incremental Learning of Word Embeddings Using Context Informativeness* (Kabbach et al., 2019). **Abstract** In this paper, we investigate the task of learning word embeddings from very sparse data in an incremental, cognitively-plausible way. We focus on the notion of informativeness, that is, the idea that some content is more valuable to the learning process than other. We further highlight the challenges of online learning and argue that previous systems fall short of implementing incrementality. Concretely, we incorporate informativeness in a previously proposed model of nonce learning, using it for context selection and learning rate modulation. We test our system on the task of learning new words from definitions, as well as on the task of learning new words from potentially uninformative contexts. We demonstrate that informativeness is crucial to obtaining state-of-the-art performance in a truly incremental setup. **Citation** ```tex @inproceedings{kabbach-etal-2019-towards, title = "Towards Incremental Learning of Word Embeddings Using Context Informativeness", author = "Kabbach, Alexandre and Gulordava, Kristina and Herbelot, Aur{\'e}lie", booktitle = "Proceedings of the 57th Conference of the Association for Computational Linguistics: Student Research Workshop", month = jul, year = "2019", address = "Florence, Italy", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/P19-2022", pages = "162--168" } ```