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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 BASE Show 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; Liu, Xiaohu; Guo, Chenlei. - : arXiv, 2022 Abstract: Voice assistants such as Alexa, Siri, and Google Assistant have become increasingly popular worldwide. However, linguistic variations, variability of speech patterns, ambient acoustic conditions, and other such factors are often correlated with the assistants misinterpreting the user's query. In order to provide better customer experience, retrieval based query reformulation (QR) systems are widely used to reformulate those misinterpreted user queries. Current QR systems typically focus on neural retrieval model training or direct entities retrieval for the reformulating. However, these methods rarely focus on query expansion and entity weighting simultaneously, which may limit the scope and accuracy of the query reformulation retrieval. In this work, we propose a novel Query Expansion and Entity Weighting method (QEEW), which leverages the relationships between entities in the entity catalog (consisting of users' queries, assistant's responses, and corresponding entities), to enhance the query reformulation ... Keyword: Artificial Intelligence cs.AI; FOS Computer and information sciences; Information Retrieval cs.IR URL: https://dx.doi.org/10.48550/arxiv.2202.13869 https://arxiv.org/abs/2202.13869 BASE Hide 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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