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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 – 20 of 20 1 Bootstrapping Multilingual AMR with Contextual Word Alignments ... Sheth, Janaki; Lee, Young-Suk; Astudillo, Ramon Fernandez. - : arXiv, 2021 BASE Show details 2 VAULT: VAriable Unified Long Text Representation for Machine Reading Comprehension ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Ferritto, Anthony; Florian, Radu. - : Underline Science Inc., 2021 BASE Show details 3 Structure-aware Fine-tuning of Sequence-to-sequence Transformers for Transition-based AMR Parsing ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Astudillo, Ramón Fernandez; Florian, Radu. - : Underline Science Inc., 2021 BASE Show details 4 Multilingual Transfer Learning for QA Using Translation as Data Augmentation ... Bornea, Mihaela; Pan, Lin; Rosenthal, Sara. - : arXiv, 2020 BASE Show details 5 GPT-too: A language-model-first approach for AMR-to-text generation ... Mager, Manuel; Astudillo, Ramon Fernandez; Naseem, Tahira. - : arXiv, 2020 BASE Show details 6 A Multilingual Reading Comprehension System for more than 100 Languages ... The 28th International Conference on Computational Linguistics 2020; Bornea, Mihaela; Chakravarti, Rishav. - : Underline Science Inc., 2020 BASE Show details 7 Neural Cross-Lingual Relation Extraction Based on Bilingual Word Embedding Mapping ... Ni, Jian; Florian, Radu. - : arXiv, 2019 BASE Show details 8 Towards Lingua Franca Named Entity Recognition with BERT ... Moon, Taesun; Awasthy, Parul; Ni, Jian. - : arXiv, 2019 BASE Show details 9 Neural Cross-Lingual Coreference Resolution and its Application to Entity Linking ... Kundu, Gourab; Sil, Avirup; Florian, Radu. - : arXiv, 2018 BASE Show details 10 Neural Cross-Lingual Entity Linking ... Sil, Avirup; Kundu, Gourab; Florian, Radu. - : arXiv, 2017 BASE Show details 11 One for All: Towards Language Independent Named Entity Linking ... Sil, Avirup; Florian, Radu. - : arXiv, 2017 BASE Show details 12 Weakly Supervised Cross-Lingual Named Entity Recognition via Effective Annotation and Representation Projection ... Ni, Jian; Dinu, Georgiana; Florian, Radu. - : arXiv, 2017 BASE Show details 13 Improving Multilingual Named Entity Recognition with Wikipedia Entity Type Mapping ... Ni, Jian; Florian, Radu. - : arXiv, 2017 BASE Show details 14 A Sentence Compression Based Framework to Query-Focused Multi-Document Summarization ... Wang, Lu; Raghavan, Hema; Castelli, Vittorio. - : arXiv, 2016 BASE Show details 15 Arabic computational linguistics Farghaly, Ali Ahmed Sabry (Hrsg.); Zitouni, Imed; Fraser, Alexander. - Stanford, Calif. : CSLI Publ., 2010 BLLDB UB Frankfurt Linguistik Show details 16 A cascaded approach to mention detection and chaining in Arabic Zitouni, Imed; Florian, Radu; Luo, Xiaoqiang In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 17 (2009) 5, 935-944 BLLDB OLC Linguistik Show details 17 HowtogetaChineseName(Entity): Segmentation and Combination Issues Jing, Hongyan; Florian, Radu; Luo, Xiaoqiang; Zhang, Tong; Ittycheriah, Abraham In: DTIC (2003) Abstract: When building a Chinese named entity recognition system, one must deal with certain language-specific issues such as whether the model should be based on characters or words. While there is no unique answer to this question, we discuss in detail advantages and disadvantages of each model, identify problems in segmentation and suggest possible solutions, presenting our observations, analysis, and experimental results. The second topic of this paper is classifier combination. We present and describe four classifiers for Chinese named entity recognition and describe various methods for combining their outputs. The results demonstrate that classifier combination is an effective technique of improving system performance: experiments over a large annotated corpus of fine-grained entity types exhibit a 10% relative reduction in F-measure error. ; Presented at the Conference on Empirical Methods in Natural Language Processing (EMNLP 2003) held in Sapporo, Japan on 11-12 Jul 2003. Published in the Proceedings of the Conference on Empirical Methods in Natural Language Processing, 2003. Sponsored in part by DARPA and National Science Foundation. Keyword: *CHINESE LANGUAGE; *CLASSIFIERS; *HMM(HIDDEN MARKOV MODEL); *NAMED ENTITY RECOGNITION; *RECOGNITION; *WORDS(LANGUAGE); ALGORITHMS; CHARACTER-BASED MODELS; CLASSIFICATION; Cybernetics; Information Science; Linguistics; MARKOV PROCESSES; MODELS; NATURAL LANGUAGE; SYMPOSIA; WORD SEGMENTATION; WORD-BASED MODELS URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA457910 http://www.dtic.mil/docs/citations/ADA457910 BASE Hide details 18 Evaluating word sense disambiguation systems Edmonds, Philip (Hrsg.); Kilgarriff, Adam (Hrsg.); Yarowsky, David (Mitarb.)... In: Natural language engineering. - Cambridge : Cambridge University Press 8 (2002) 4, 279-390 BLLDB Show details 19 Named Entity Recognition as a House of Cards: Classifier Stacking Florian, Radu In: DTIC (2002) BASE Show details 20 Dynamic Nonlocal Language Modeling via Hierarchical Topic-Based Adaptation ... Florian, Radu; Yarowsky, David. - : arXiv, 2001 BASE Show details

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