Page: 1 2 3 4 5 6 7 8 9... 429
82 |
Cambridge Psycholinguistic Inventory of Christian Beliefs: A registered report of construct validity, internal consistency and test-retest reliability
|
|
|
|
BASE
|
|
Show details
|
|
83 |
HMong Parent Day/Hnub Txhawb Nqa Niam Txiv: Implementing Psychosociocultural Educational Programming to Honor Rau Siab
|
|
|
|
In: Journal of Southeast Asian American Education and Advancement (2022)
|
|
BASE
|
|
Show details
|
|
84 |
Knowledge Building with Low Proficiency English Language Learners: Facilitating Metalinguistic Awareness and Scientific Understanding in Parallel
|
|
|
|
BASE
|
|
Show details
|
|
86 |
[In Press] Quality and integrity in the translation of official documents
|
|
|
|
BASE
|
|
Show details
|
|
87 |
Método de Abordajes Lingüísticos Convergentes para el ACD: una propuesta aplicada al análisis de comentarios digitales
|
|
|
|
In: Onomázein: Revista de lingüística, filología y traducción de la Pontificia Universidad Católica de Chile, ISSN 0718-5758, Nº. 55, 2022, pags. 92-114 (2022)
|
|
BASE
|
|
Show details
|
|
88 |
nutsamaat uy’skwuluwun: Coast Salish pedagogy in higher education
|
|
|
|
BASE
|
|
Show details
|
|
89 |
Neural-based Knowledge Transfer in Natural Language Processing
|
|
|
|
Abstract:
In Natural Language Processing (NLP), neural-based knowledge transfer, which is to transfer out-of-domain (OOD) knowledge to task-specific neural networks, has been applied to many NLP tasks. To further explore neural-based knowledge transfer in NLP, in this dissertation, we consider both structured OOD knowledge and unstructured OOD knowledge, and deal with several representative NLP tasks. For structured OOD knowledge, we study the neural-based knowledge transfer in Machine Reading Comprehension (MRC). In single-passage MRC tasks, to bridge the gap between MRC models and human beings, which is mainly reflected in the hunger for data and the robustness to noise, we integrate the neural networks of MRC models with the general knowledge of human beings embodied in knowledge bases. On the one hand, we propose a data enrichment method, which uses WordNet to extract inter-word semantic connections as general knowledge from each given passage-question pair. On the other hand, we propose a novel MRC model named Knowledge Aided Reader (KAR), which explicitly uses the above extracted general knowledge to assist its attention mechanisms. According to the experimental results, KAR is comparable in performance with the state-of-the-art MRC models, and significantly more robust to noise than them. On top of that, when only a subset (20%-80%) of the training examples are available, KAR outperforms the state-of-the-art MRC models by a large margin, and is still reasonably robust to noise. In multi-hop MRC tasks, to probe the strength of Graph Neural Networks (GNNs), we propose a novel multi-hop MRC model named Graph Aided Reader (GAR), which uses GNN methods to perform multi-hop reasoning, but is free of any pre-trained language model and completely end-to-end. For graph construction, GAR utilizes the topic-referencing relations between passages and the entity-sharing relations between sentences, which is aimed at obtaining the most sensible reasoning clues. For message passing, GAR simulates a top-down reasoning and a bottom-up reasoning, which is aimed at making the best use of the above obtained reasoning clues. According to the experimental results, GAR even outperforms several competitors relying on pre-trained language models and filter-reader pipelines, which implies that GAR benefits a lot from its GNN methods. On this basis, GAR can further benefit from applying pre-trained language models, but pre-trained language models can mainly facilitate the within-passage reasoning rather than cross-passage reasoning of GAR. Moreover, compared with the competitors constructed as filter-reader pipelines, GAR is not only easier to train, but also more applicable to the low-resource cases. For unstructured OOD knowledge, we study the neural-based knowledge transfer in Natural Language Understanding (NLU), and focus on the neural-based knowledge transfer between languages, which is also known as Cross-Lingual Transfer Learning (CLTL). To facilitate the CLTL of NLU models, especially the CLTL between distant languages, we propose a novel CLTL model named Translation Aided Language Learner (TALL), where CLTL is integrated with Machine Translation (MT). Specifically, we adopt a pre-trained multilingual language model as our baseline model, and construct TALL by appending a decoder to it. On this basis, we directly fine-tune the baseline model as an NLU model to conduct CLTL, but put TALL through an MT-oriented pre-training before its NLU-oriented fine-tuning. To make use of unannotated data, we implement the recently proposed Unsupervised Machine Translation (UMT) technique in the MT-oriented pre-training of TALL. According to the experimental results, the application of UMT enables TALL to consistently achieve better CLTL performance than the baseline model without using more annotated data, and the performance gain is relatively prominent in the case of distant languages.
|
|
Keyword:
Cross-lingual transfer learning; Graph neural network; Information technology; Knowledge base; Knowledge graph; Knowledge transfer; Machine Reading Comprehension; Multi-hop reasoning; Natural Language Processing; Natural language understanding; Neural network; unsupervised machine translation
|
|
URL: http://hdl.handle.net/10315/39096
|
|
BASE
|
|
Hide details
|
|
90 |
A BDI Empathic Agent Model Based on a Multidimensional Cross-Cultural Emotion Representation
|
|
|
|
BASE
|
|
Show details
|
|
92 |
Ranking Semantics for Argumentation Systems With Necessities
|
|
|
|
In: IJCAI 2020 - 29th International Joint Conference on Artificial Intelligence ; https://hal.archives-ouvertes.fr/hal-03002056 ; IJCAI 2020 - 29th International Joint Conference on Artificial Intelligence, Jan 2021, Yokohama / Virtual, Japan. pp.1912-1918, ⟨10.24963/ijcai.2020/265⟩ (2021)
|
|
BASE
|
|
Show details
|
|
93 |
From reduced artificial intelligence to semiotic engineering ; From reduced artificial intelligence to semiotic engineering: a new project for artificial intelligence
|
|
|
|
In: https://hal.archives-ouvertes.fr/hal-03450318 ; 2021 (2021)
|
|
BASE
|
|
Show details
|
|
94 |
A Navigation Tool for Exploring Semantic Web Corpora
|
|
|
|
In: Proceedings of the ISWC 2021 Posters, Demos and Industry Tracks ; https://hal.univ-lorraine.fr/hal-03485155 ; Proceedings of the ISWC 2021 Posters, Demos and Industry Tracks, Oct 2021, Virtual conference, France (2021)
|
|
BASE
|
|
Show details
|
|
95 |
A Semantic Web Navigation Tool for Exploring the Henri Poincaré Correspondence Corpus
|
|
|
|
In: Proceedings of the International Joint Workshop on Semantic Web and Ontology Design for Cultural Heritage ; https://hal.univ-lorraine.fr/hal-03406713 ; Proceedings of the International Joint Workshop on Semantic Web and Ontology Design for Cultural Heritage, Antonis Bikakis, Roberta Ferrario, Stéphane Jean, Béatrice Markhoff, Alessandro Mosca, Marianna and Nicolosi Asmundo, Sep 2021, Bolzano, Italy (2021)
|
|
BASE
|
|
Show details
|
|
96 |
Non-English languages enrich scientific knowledge: The example of economic costs of biological invasions
|
|
|
|
In: ISSN: 0048-9697 ; EISSN: 1879-1026 ; Science of the Total Environment ; https://hal.archives-ouvertes.fr/hal-03192043 ; Science of the Total Environment, Elsevier, 2021, 775, pp.144441. ⟨10.1016/j.scitotenv.2020.144441⟩ ; https://reader.elsevier.com/reader/sd/pii/S0048969720379729 (2021)
|
|
BASE
|
|
Show details
|
|
97 |
Using Digital Games in the Science Classroom
|
|
|
|
In: Boise State University Theses and Dissertations (2021)
|
|
BASE
|
|
Show details
|
|
98 |
The Role of Traditional Plant Knowledge in the Fight Against Infectious Diseases: A Meta-Analytic Study in the Catalan Linguistic Area
|
|
|
|
BASE
|
|
Show details
|
|
99 |
The Dragoman Renaissance: Diplomatic Interpreters and the Routes of Orientalism
|
|
|
|
BASE
|
|
Show details
|
|
100 |
A Knowledge Compilation Map for Conditional Preference Statements-based Languages
|
|
|
|
In: Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems ; 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021) ; https://hal.archives-ouvertes.fr/hal-03160469 ; 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021), International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), May 2021, Londres (virtual), United Kingdom ; https://aamas2021.soton.ac.uk/ (2021)
|
|
BASE
|
|
Show details
|
|
Page: 1 2 3 4 5 6 7 8 9... 429
|
|