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Corpus-based Language Universals Analysis using Universal Dependencies ; Analyse orientée corpus d'universaux linguistiques sur Universal Dependencies
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In: SyntaxFest Quasy 2021 - Quantitative Syntax ; https://hal.inria.fr/hal-03501774 ; SyntaxFest Quasy 2021 - Quantitative Syntax, Mar 2022, Sofia, Bulgaria (2022)
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Corpus-based Language Universals Analysis using Universal Dependencies ; Analyse orientée corpus d'universaux linguistiques sur Universal Dependencies
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In: Quasy (Quantitative Syntax), SyntaxFest 2021 ; https://hal.inria.fr/hal-03501774 ; Quasy (Quantitative Syntax), SyntaxFest 2021, Mar 2022, Sofia, Bulgaria (2022)
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The Role Of Language On knowledge Transfer In Multinational Enterprises (MNEs) ...
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Choi, Yoona. - : The Australian National University, 2022
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MSCCD: Grammar Pluggable Clone Detection Based on ANTLR Parser Generation ...
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A Feasibility Study of Answer-Agnostic Question Generation for Education ...
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WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation ...
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Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps ...
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Interactive Robotic Grasping with Attribute-Guided Disambiguation ...
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Finding Inverse Document Frequency Information in BERT ...
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Abstract:
For many decades, BM25 and its variants have been the dominant document retrieval approach, where their two underlying features are Term Frequency (TF) and Inverse Document Frequency (IDF). The traditional approach, however, is being rapidly replaced by Neural Ranking Models (NRMs) that can exploit semantic features. In this work, we consider BERT-based NRMs and study if IDF information is present in the NRMs. This simple question is interesting because IDF has been indispensable for the traditional lexical matching, but global features like IDF are not explicitly learned by neural language models including BERT. We adopt linear probing as the main analysis tool because typical BERT based NRMs utilize linear or inner-product based score aggregators. We analyze input embeddings, representations of all BERT layers, and the self-attention weights of CLS. By studying MS-MARCO dataset with three BERT-based models, we show that all of them contain information that is strongly dependent on IDF. ... : 5 pages ...
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Keyword:
FOS Computer and information sciences; H.3.3; Information Retrieval cs.IR
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URL: https://arxiv.org/abs/2202.12191
https://dx.doi.org/10.48550/arxiv.2202.12191
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COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics ...
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| 11 |
Survival in Korean Patients with Frontotemporal Dementia Syndrome: Association with Behavioral Features and Parkinsonism
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In: Journal of Clinical Medicine; Volume 11; Issue 8; Pages: 2260 (2022)
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How Will Video Conference Fatigue Affect Participants of MICE in the With-COVID-19 Era? Focusing on Video Conference Quality, Social Presence Theory, and Flow
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In: International Journal of Environmental Research and Public Health; Volume 19; Issue 8; Pages: 4601 (2022)
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How We Failed in Context: A Text-Mining Approach to Understanding Hotel Service Failures
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In: Sustainability; Volume 14; Issue 5; Pages: 2675 (2022)
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Ear, Nose, and Throat Foreign Bodies in Children: A Retrospective Study
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In: Children; Volume 9; Issue 1; Pages: 63 (2022)
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Emphasizing Multilingualism in Teacher Education Courses: Teacher Candidates’ Responses to Translanguaging Pedagogy
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In: SoTL Commons Conference (2022)
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Development and Validation of the Radiology Common Data Model (R-CDM) for the International Standardization of Medical Imaging Data
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In: Yonsei Med J (2022)
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| 17 |
Association between sleep parameters and longitudinal shortening of telomere length
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In: Aging (Albany NY) (2022)
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When danger strikes: A linguistic tool for tracking America’s collective response to threats
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In: Proc Natl Acad Sci U S A (2022)
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Results of Active Middle Ear Implantation in Patients With Mixed Hearing Loss After Middle Ear Surgery: A Prospective Multicenter Study (the ROMEO Study)
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In: Clin Exp Otorhinolaryngol (2022)
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