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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 Page: 1 2 3 4 5...32 Hits 1 – 20 of 626 1 Cross-media Scientific Research Achievements Query based on Ranking Learning ... Wang, Benzhi; Liang, Meiyu; Li, Ang. - : arXiv, 2022 BASE Show details 2 Exploring Sub-skeleton Trajectories for Interpretable Recognition of Sign Language ... Gudmundsson, Joachim; Seybold, Martin P.; Pfeifer, John. - : arXiv, 2022 BASE Show details 3 Cross-Lingual Query-Based Summarization of Crisis-Related Social Media: An Abstractive Approach Using Transformers ... Vitiugin, Fedor; Castillo, Carlos. - : arXiv, 2022 BASE Show details 4 Simplifying Multilingual News Clustering Through Projection From a Shared Space ... Santos, João; Mendes, Afonso; Miranda, Sebastião. - : arXiv, 2022 BASE Show details 5 Towards Best Practices for Training Multilingual Dense Retrieval Models ... Zhang, Xinyu; Ogueji, Kelechi; Ma, Xueguang. - : arXiv, 2022 BASE Show details 6 Addressing Issues of Cross-Linguality in Open-Retrieval Question Answering Systems For Emergent Domains ... Albalak, Alon; Levy, Sharon; Wang, William Yang. - : arXiv, 2022 Abstract: Open-retrieval question answering systems are generally trained and tested on large datasets in well-established domains. However, low-resource settings such as new and emerging domains would especially benefit from reliable question answering systems. Furthermore, multilingual and cross-lingual resources in emergent domains are scarce, leading to few or no such systems. In this paper, we demonstrate a cross-lingual open-retrieval question answering system for the emergent domain of COVID-19. Our system adopts a corpus of scientific articles to ensure that retrieved documents are reliable. To address the scarcity of cross-lingual training data in emergent domains, we present a method utilizing automatic translation, alignment, and filtering to produce English-to-all datasets. We show that a deep semantic retriever greatly benefits from training on our English-to-all data and significantly outperforms a BM25 baseline in the cross-lingual setting. We illustrate the capabilities of our system with examples and ... : 6 pages, 8 figures ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Information Retrieval cs.IR URL: https://arxiv.org/abs/2201.11153 https://dx.doi.org/10.48550/arxiv.2201.11153 BASE Hide details 7 C3: Continued Pretraining with Contrastive Weak Supervision for Cross Language Ad-Hoc Retrieval ... Yang, Eugene; Nair, Suraj; Chandradevan, Ramraj. - : arXiv, 2022 BASE Show details 8 Parameter-Efficient Neural Reranking for Cross-Lingual and Multilingual Retrieval ... Litschko, Robert; Vulić, Ivan; Glavaš, Goran. - : arXiv, 2022 BASE Show details 9 QALD-9-plus: A Multilingual Dataset for Question Answering over DBpedia and Wikidata Translated by Native Speakers ... Perevalov, Aleksandr; Diefenbach, Dennis; Usbeck, Ricardo. - : arXiv, 2022 BASE Show details 10 MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Dataset ... Nielsen, Dan Saattrup; McConville, Ryan. - : arXiv, 2022 BASE Show details 11 From Examples to Rules: Neural Guided Rule Synthesis for Information Extraction ... Vacareanu, Robert; Valenzuela-Escarcega, Marco A.; Barbosa, George C. G.. - : arXiv, 2022 BASE Show details 12 Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations ... Meng, Yu; Zhang, Yunyi; Huang, Jiaxin. - : arXiv, 2022 BASE Show details 13 Offensive Language Detection in Under-resourced Algerian Dialectal Arabic Language ... Boucherit, Oussama; Abainia, Kheireddine. - : arXiv, 2022 BASE Show details 14 Shedding New Light on the Language of the Dark Web ... Jin, Youngjin; Jang, Eugene; Lee, Yongjae. - : arXiv, 2022 BASE Show details 15 Query Expansion and Entity Weighting for Query Reformulation Retrieval in Voice Assistant Systems ... Sun, Zhongkai; Lu, Sixing; Ma, Chengyuan. - : arXiv, 2022 BASE Show details 16 LoL: A Comparative Regularization Loss over Query Reformulation Losses for Pseudo-Relevance Feedback ... Zhu, Yunchang; Pang, Liang; Lan, Yanyan. - : arXiv, 2022 BASE Show details 17 Finding Inverse Document Frequency Information in BERT ... Choi, Jaekeol; Jung, Euna; Lim, Sungjun. - : arXiv, 2022 BASE Show details 18 Improving Word Translation via Two-Stage Contrastive Learning ... Li, Yaoyiran; Liu, Fangyu; Collier, Nigel. - : arXiv, 2022 BASE Show details 19 nigam@COLIEE-22: Legal Case Retrieval and Entailment using Cascading of Lexical and Semantic-based models ... Nigam, Shubham Kumar; Goel, Navansh. - : arXiv, 2022 BASE Show details 20 Out-of-Domain Semantics to the Rescue! Zero-Shot Hybrid Retrieval Models ... Chen, Tao; Zhang, Mingyang; Lu, Jing. - : arXiv, 2022 BASE Show details Page: 1 2 3 4 5...32

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