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Jibes & Delights: A Dataset of Targeted Insults and Compliments to Tackle Online Abuse ...
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Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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Phrase-Level Action Reinforcement Learning for Neural Dialog Response Generation ...
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Correcting Chinese Spelling Errors with Phonetic Pre-training ...
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PLOME: Pre-training with Misspelled Knowledge for Chinese Spelling Correction ...
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Including Signed Languages in Natural Language Processing ...
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When is Char Better Than Subword: A Systematic Study of Segmentation Algorithms for Neural Machine Translation ...
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To POS Tag or Not to POS Tag: The Impact of POS Tags on Morphological Learning in Low-Resource Settings ...
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Superbizarre Is Not Superb: Derivational Morphology Improves BERT's Interpretation of Complex Words ...
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HIT - A Hierarchically Fused Deep Attention Network for Robust Code-mixed Language Representation ...
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Minimally-Supervised Morphological Segmentation using Adaptor Grammars with Linguistic Priors ...
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LearnDA: Learnable Knowledge-Guided Data Augmentation for Event Causality Identification ...
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Quotation Recommendation and Interpretation Based on Transformation from Queries to Quotations ...
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How Did This Get Funded?! Automatically Identifying Quirky Scientific Achievements ...
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Minimax and Neyman–Pearson Meta-Learning for Outlier Languages ...
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CLINE: Contrastive Learning with Semantic Negative Examples for Natural Language Understanding ...
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Towards Protecting Vital Healthcare Programs by Extracting Actionable Knowledge from Policy ...
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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; ., Marco Luca; Brady, sebrady3@ie.ibm.com; Carroll, Eoin; Lam, Hoang Thanh; Lopez, Vanessa; Picco, Gabriele; Segrave, John; Vejsbjerg, Inge; Wei, Miao; Yadavb, Nagesh. - : Underline Science Inc., 2021
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Abstract:
Read paper: https://www.aclanthology.org/2021.findings-acl.308 Abstract: In challenging economic times, obtaining value for money by ensuring financial integrity and fairer distribution of services are among the top priorities for social and health-care systems globally. However, healthcare billing policies are complex and identifying non-compliance is often narrow-scope, manual and expensive. Maintaining ‘integrity’ is a challenge - ensuring that scarce resources get to those in need and are not lost to fraud and waste. Our approach fuses recent advances in dependency parsing with a policy ontology to convert the content of regulatory healthcare policy into human-friendly policy rules, that are amenable to machine-execution, with human oversight. We describe the ontology-guided transformation of textual patterns into a semantically-meaningful knowledge graph of rules, outline our experiments and evaluate results against policy rules obtained from professional investigators. The aim is to make a ...
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Keyword:
Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
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URL: https://dx.doi.org/10.48448/zfk0-ad41 https://underline.io/lecture/26399-towards-protecting-vital-healthcare-programs-by-extracting-actionable-knowledge-from-policy
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DYPLOC: Dynamic Planning of Content Using Mixed Language Models for Text Generation ...
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Automated Concatenation of Embeddings for Structured Prediction ...
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QASR: QCRI Aljazeera Speech Resource A Large Scale Annotated Arabic Speech Corpus ...
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