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Improving Text Understanding via Deep Syntax-Semantics Communication
2020
Findings of the Association for Computational Linguistics: EMNLP 2020
unpublished
Preserved Fulltext
In this paper, we propose a deep neural communication model between syntax and semantics to improve the performance of text understanding. ...
Recent studies show that integrating syntactic tree models with sequential semantic models can bring improved task performance, while these methods mostly employ shallow integration of syntax and semantics ...
Conclusion We proposed a deep syntax-semantics communication model for improving text understanding. ...
doi:10.18653/v1/2020.findings-emnlp.8
fatcat:afibqyaczzcr7hnngbb6wl5q2y
AllenNLP: A Deep Semantic Natural Language Processing Platform
[article]
2018
arXiv
pre-print
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This paper describes AllenNLP, a platform for research on deep learning methods in natural language understanding. ...
It also includes reference implementations of high quality approaches for both core semantic problems (e.g. semantic role labeling (Palmer et al., 2005)) and language understanding applications (e.g. machine ...
ELMo is a deep contextualized word representation that models both complex characteristics of word use (e.g., syntax and semantics) and how these uses vary across linguistic contexts (in order to model ...
arXiv:1803.07640v2
fatcat:cqmoemq4kvgj7i4bnks3pivdo4
A common type system for clinical natural language processing
2013
Journal of Biomedical Semantics
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Conclusions: We have created a type system that targets deep semantics, thereby allowing for NLP systems to encapsulate knowledge from text and share it alongside heterogenous clinical data sources. ...
Rather than surface semantics that are typically the end product of NLP algorithms, CEM-based semantics explicitly build in deep clinical semantics as the point of interoperability with more structured ...
We eventually modified existing types and categorized them into 4 groupings: Utilities, Text Spans, Syntax, and Text Semantics. ...
doi:10.1186/2041-1480-4-1
pmid:23286462
pmcid:PMC3575354
fatcat:4zvqlql3wfh2vmombjmcp76dsq
Rapid Text-Based Authoring of Defeasible Higher-Order Logic Formulas, via Textual Logic and Rulelog
[chapter]
2013
Lecture Notes in Computer Science
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We present textual logic (TL), a novel approach that enables rapid semi-automatic acquisition of rich logical knowledge from text. ...
Another key element of TL is a method for rapid interactive disambiguation as part of logic-based text interpretation. ...
Third, sharability: particularly when semantic and semantic-web-friendly, it facilitates reusability and merging of larger KB's, via knowledge interchange. ...
doi:10.1007/978-3-642-39617-5_2
fatcat:avpuxhcqebfb3jcprkjwynuffm
CSSAM:Code Search via Attention Matching of Code Semantics and Structures
[article]
2022
arXiv
pre-print
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syntax tree nodes and the data flow of the codes. ...
Second, there is a potential semantic relationship between code and query, it is challenging to align code and text across sequences so that vectors are spatially consistent during similarity matching. ...
Understanding the semantics of code through words alone often fails to understand the deeper semantic information expressed in code. ...
arXiv:2208.03922v1
fatcat:hffcsy52anhkteec53o4s2lwd4
A Minimalist Dataset for Systematic Generalization of Perception, Syntax, and Semantics
[article]
2022
arXiv
pre-print
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, and semantics. ...
Moreover, we find that it is infeasible to solve HINT by simply scaling up the dataset and the model size; this strategy barely helps the extrapolation over syntax and semantics. ...
Dataset Domain Task Modality Perception Syntax Semantics Generalization Size SCAN [57] synthetic SP text systematic 100K gSCAN [81] synthetic SP i&t * systematic 300K PCFG [43] synthetic SP text ...
arXiv:2103.01403v2
fatcat:hqkagnsnybcg7cmalj662xsfpe
Are Deep Learning Approaches Suitable for Natural Language Processing?
[chapter]
2016
Lecture Notes in Computer Science
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All these reviewed topics have been limited to show contributions to text understanding, such as sentence modelling, sentiment classification, semantic role labelling, question answering, etc. ...
In recent years, Deep Learning (DL) techniques have gained much attention from Artificial Intelligence (AI) and Natural Language Processing (NLP) research communities because these approaches can often ...
Text Understanding Task
ANNs
CNNs
RNNs
Sentence Classification
✔
Named Entity Recognition (NER)
✔
Text Categorization
✔
Semantic Role Labelling
✔
Semantic Clustering
✔
Short-Text Conversation ...
doi:10.1007/978-3-319-41754-7_33
fatcat:ssbeueae2fh6vpexuehm5u5cna
Columns Occurrences Graph to Improve Column Prediction in Deep Learning Nlidb
2021
Applied Sciences
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Deep learning has shown potential for rapid growth and improvement in text-to-SQL tasks. ...
Working towards closing the semantic gap between user intention and predicted columns, we present an approach for deep learning text-to-SQL tasks that includes previous columns' occurrences scores as an ...
Decoders of the model predict the SQL syntax via a grammar to call modules based on history tokens. ...
doi:10.3390/app112412116
fatcat:a273hqtdvbactkzn7npsi6h3tm
Conversational artificial intelligence - demystifying statistical vs linguistic NLP solutions
2020
Journal of Computer-Assisted Linguistic Research
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This is explored via a text based conversational software agents with a deep strategic role to hold a conversation and enable the mechanisms need to plan, and to decide what to do next, and manage the ...
Both are slowly emerging as a real presence in our lives from the impressive technological developments in machine learning, deep learning and natural language understanding solutions. ...
The linking system will facilitate procedures for semantic-to-syntax and syntax-to-semantics, parsing and in the process of formulating a grammatical correct response. ...
doi:10.4995/jclr.2020.12932
fatcat:oogpuyd6zvhixi22k33xawe3dm
A Survey of Automatic Software Vulnerability Detection, Program Repair, and Defect Prediction Techniques
2020
Security and Communication Networks
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The development of deep learning technology has brought new opportunities for the study of potential security issues in software, and researchers have successively proposed many automation methods. ...
At the same time, we point out some problems of these research methods, give corresponding solutions, and finally look forward to the application prospect of deep learning technology in automated software ...
Security and Communication Networks In order to overcome the semantic incomprehensibility of patch collection generated by semantic patch technology, literature [33] mines semantic-related repair patterns ...
doi:10.1155/2020/8858010
fatcat:obeiw4p7afan5m24ydmdkmyhbm
MACHINE TRANSLATION AND MACHINE‐AIDED TRANSLATION
1978
Journal of Documentation
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Translation is indirect via some kind of 'intermediary language' or via a transfer component operating upon 'deep syntactic' or semantic representations of SL texts and producing equivalent representations ...
as to translate from scratch. 59 The situation is only marginally improved if revision is done at a console via text-editing procedures, as is under development for SYSTRAN; 175 the retyping of the ...
doi:10.1108/eb026657
fatcat:3qdsjriq5nfgzoxohhhou4lpda
Difference between Written and Spoken Czech: The Case of Verbal Nouns Denoting an Action
2017
Prague Bulletin of Mathematical Linguistics
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The present paper extends understanding of differences in expressing actions by verbal nouns in corpora of written vs. spoken Czech, namely in the Czech part of the Prague Czech-English Dependency Treebank ...
combinations of participants modifying verbal nouns; although the written corpus shows higher relative frequencies, the order of the relative frequencies of particular combinations is the same in both types of communication ...
based annotation on the highest, deep syntax layer (so-called tectogrammatical layer). ...
doi:10.1515/pralin-2017-0002
fatcat:psq72xcbdvboxoi3ygn4htqz4e
RestKB: A Library of Commonsense Knowledge about Dining at a Restaurant
2019
Electronic Proceedings in Theoretical Computer Science
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2019 pre-print arXiv:1909.08239v1 fatcat:os7ajjwpwjdodhyxle4qa62nni
This paper presents a library of commonsense knowledge, RestKB, developed in modular action language ALM and containing background knowledge relevant to the understanding of restaurant narratives, including ...
We show that encoding the knowledge base in ALM facilitates its piecewise construction and testing, and improves the generality and quality of the captured information, in comparison to an initial ASP ...
ALM and the Identified Features The syntax and semantics of modular action language ALM cover features 1-3 above. ...
doi:10.4204/eptcs.306.19
fatcat:wsm4qnuyojdtphpi2cwxouhgy4
A Review of NLIDB with Deep Learning: Findings, Challenges and Open Issues
2022
IEEE Access
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Previously they were built based on domain-specific ontologies via pipelining methods. Recently a rising variety of Deep learning ideas and techniques brought this area to the attention again. ...
Text to SQL task is also crucial because of its economic and industrial value. Natural Language Interface to Database (NLIDB) is the system that supports the text-to-SQL task. ...
Each slot is predicted and filled one at a time via separate prediction modules. This way, the model takes care of syntax issues separately and can focus more on semantic issues with given syntax. ...
doi:10.1109/access.2022.3147586
fatcat:5c3fsafclbgglb23vwbrwdmq4m
Generative Face Video Coding Techniques and Standardization Efforts: A Review
[article]
2023
arXiv
pre-print
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Generative Face Video Coding (GFVC) techniques can exploit the compact representation of facial priors and the strong inference capability of deep generative models, achieving high-quality face video communication ...
This paper conducts a comprehensive survey on the recent advances of the GFVC techniques and standardization efforts, which could be applicable to ultra low bitrate communication, user-specified animation ...
Designs an ultra-low bitrate digital human char- C3DFD [28] DCC 2022 Facial Semantics acter communication paradigm via compact 3D face descriptors. ...
arXiv:2311.02649v1
fatcat:ptm75kiegnfa5buf6y62w7o53i
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