• Refine your search:
  • 
    Keyword
  • 
    Creator / Publisher
  • 
    Year
  • 
    Medium
  • 
    Type
  • 
    BLLDB-Access:
    • free (5)
    • subject to license (0)

Search in the Catalogues and Directories

All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 5 of 5 1 Improving Word Translation via Two-Stage Contrastive Learning ... Li, Yaoyiran; Liu, Fangyu; Collier, Nigel. - : arXiv, 2022 BASE Show details 2 Emergent Communication Pretraining for Few-Shot Machine Translation ... Li, Yaoyiran; Ponti, Edoardo M.; Vulić, Ivan. - : arXiv, 2020 BASE Show details 3 Emergent Communication Pretraining for Few-Shot Machine Translation ... Li, Yaoyiran; Ponti, Edoardo; Vulic, Ivan. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 4 Emergent Communication Pretraining for Few-Shot Machine Translation ... The 28th International Conference on Computational Linguistics 2020; Korhonen, Anna; Li, Yaoyiran; Ponti, Edoardo; Vulić, Ivan. - : Underline Science Inc., 2020 Abstract: While state-of-the-art models that rely upon massively multilingual pretrained encoders achieve sample efficiency in downstream applications, they still require abundant amounts of unlabelled text. Nevertheless, most of the world's languages lack such resources. Hence, we investigate a more radical form of unsupervised knowledge transfer in the absence of linguistic data. In particular, for the first time we pretrain neural networks via emergent communication from referential games. Our key assumption is that grounding communication on images---as a crude approximation of real-world environments---inductively biases the model towards learning natural languages. On the one hand, we show that this substantially benefits machine translation in few-shot settings. On the other hand, this also provides an extrinsic evaluation protocol to probe the properties of emergent languages \textit{ex vitro}. Intuitively, the closer they are to natural languages, the higher the gains from pretraining on them should be. For ... Keyword: Computer and Information Science; Natural Language Processing; Neural Network URL: https://underline.io/lecture/6290-emergent-communication-pretraining-for-few-shot-machine-translation https://dx.doi.org/10.48448/13e8-dh54 BASE Hide details 5 Emergent Communication Pretraining for Few-Shot Machine Translation Vulic, Ivan; Ponti, Edoardo; Korhonen, Anna. - : International Committee on Computational Linguistics, 2020. : https://www.aclweb.org/anthology/2020.coling-main.416, 2020. : Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), 2020 BASE Show details

Mobile view All Catalogues UB Frankfurt Linguistik 0 IDS Mannheim 0 OLC Linguistik 0 UB Frankfurt Retrokatalog 0 DNB Subject Category Language 0 Institut für Empirische Sprachwissenschaft 0 Leibniz-Centre General Linguistics (ZAS) 0 Bibliographies BLLDB 0 BDSL 0 IDS Bibliografie zur deutschen Grammatik 0 IDS Bibliografie zur Gesprächsforschung 0 IDS Konnektoren im Deutschen 0 IDS Präpositionen im Deutschen 0 IDS OBELEX meta 0 MPI-SHH Linguistics Collection 0 MPI for Psycholinguistics 0 Linked Open Data catalogues Annohub 0 Online resources Link directory 0 Journal directory 0 Database directory 0 Dictionary directory 0 Open access documents BASE 5 Linguistik-Repository 0 IDS Publikationsserver 0 Online dissertations 0 Language Description Heritage 0