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    • Glavaš, Goran (3)
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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 – 3 of 3 1 Parameter-Efficient Neural Reranking for Cross-Lingual and Multilingual Retrieval ... Litschko, Robert; Vulić, Ivan; Glavaš, Goran. - : arXiv, 2022 BASE Show details 2 Geographic Adaptation of Pretrained Language Models ... Hofmann, Valentin; Glavaš, Goran; Ljubešić, Nikola; Pierrehumbert, Janet B.; Schütze, Hinrich. - : arXiv, 2022 Abstract: Geographic linguistic features are commonly used to improve the performance of pretrained language models (PLMs) on NLP tasks where geographic knowledge is intuitively beneficial (e.g., geolocation prediction and dialect feature prediction). Existing work, however, leverages such geographic information in task-specific fine-tuning, failing to incorporate it into PLMs' geo-linguistic knowledge, which would make it transferable across different tasks. In this work, we introduce an approach to task-agnostic geoadaptation of PLMs that forces the PLM to learn associations between linguistic phenomena and geographic locations. More specifically, geoadaptation is an intermediate training step that couples masked language modeling and geolocation prediction in a dynamic multitask learning setup. In our experiments, we geoadapt BERTić -- a PLM for Bosnian, Croatian, Montenegrin, and Serbian (BCMS) -- using a corpus of geotagged BCMS tweets. Evaluation on three different tasks, namely unsupervised (zero-shot) and ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2203.08565 https://dx.doi.org/10.48550/arxiv.2203.08565 BASE Hide details 3 On cross-lingual retrieval with multilingual text encoders Litschko, Robert; Vulić, Ivan; Ponzetto, Simone Paolo. - : Springer Science + Business Media, 2022 BASE Show details

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