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A Survey of Knowledge Enhanced Pre-trained Language Models

https://doi.org/10.1145/3631392
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Outgoing claims: the papers this work cites, builds on, or argues with.

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An Introduction to the Resource Description Framework
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Mixed Pooling for Convolutional Neural Networks
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CN-DBpedia: A Never-Ending Chinese Knowledge Extraction System
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A semantic matching energy function for learning with multi-relational data
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Building large knowledge-based systems: Representation and inference in the cyc project
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A FRAMEWORK FOR REPRESENTING KNOWLEDGE
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CokeBERT: Contextual knowledge selection and embedding towards enhanced pre-trained language models
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Semi-lexical languages: a formal basis for using domain knowledge to resolve ambiguities in deep-learning based computer vision
inferredcites →https://doi.org/10.1109/tnnls.2021.3070843openalex-snapshot
A Survey on Knowledge Graphs: Representation, Acquisition, and Applications
inferredcites →https://doi.org/10.1109/tpami.2017.2754246openalex-snapshot
FVQA: Fact-Based Visual Question Answering
inferredcites →https://doi.org/10.1145/219717.219748openalex-snapshot
WordNet
inferredcites →https://doi.org/10.1145/3442381.3450141openalex-snapshot
Inductive Entity Representations from Text via Link Prediction
inferredcites →https://doi.org/10.1162/tacl_a_00051openalex-snapshot
Enriching Word Vectors with Subword Information
inferredcites →https://doi.org/10.1162/tacl_a_00302openalex-snapshot
A Knowledge-Enhanced Pretraining Model for Commonsense Story Generation
inferredcites →https://doi.org/10.1162/tacl_a_00342openalex-snapshot
oLMpics-On What Language Model Pre-training Captures
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A Primer in BERTology: What We Know About How BERT Works
inferredcites →https://doi.org/10.1162/tacl_a_00360openalex-snapshot
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation
inferredcites →https://doi.org/10.1561/9781601982957openalex-snapshot
Learning Deep Architectures for AI
inferredcites →https://doi.org/10.1609/aaai.v28i1.8870openalex-snapshot
Knowledge Graph Embedding by Translating on Hyperplanes
inferredcites →https://doi.org/10.1609/aaai.v29i1.9491openalex-snapshot
Learning Entity and Relation Embeddings for Knowledge Graph Completion
inferredcites →https://doi.org/10.1609/aaai.v30i1.10314openalex-snapshot
Holographic Embeddings of Knowledge Graphs
inferredcites →https://doi.org/10.1609/aaai.v32i1.11573openalex-snapshot
Convolutional 2D Knowledge Graph Embeddings
inferredcites →https://doi.org/10.1609/aaai.v33i01.33013060openalex-snapshot
End-to-End Structure-Aware Convolutional Networks for Knowledge Base Completion
inferredcites →https://doi.org/10.1609/aaai.v34i03.5681openalex-snapshot
K-BERT: Enabling Language Representation with Knowledge Graph
inferredcites →https://doi.org/10.1609/aaai.v34i05.6428openalex-snapshot
ERNIE 2.0: A Continual Pre-Training Framework for Language Understanding
inferredcites →https://doi.org/10.1609/aaai.v35i7.16796openalex-snapshot
KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning
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Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
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Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
inferredcites →https://doi.org/10.18653/v1/2020.coling-mainopenalex-snapshot
Proceedings of the 28th International Conference on Computational Linguistics
inferredcites →https://doi.org/10.18653/v1/2020.coling-main.327openalex-snapshot
CoLAKE: Contextualized Language and Knowledge Embedding
inferredcites →https://doi.org/10.18653/v1/2020.emnlp-mainopenalex-snapshot
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
inferredcites →https://doi.org/10.18653/v1/2020.emnlp-main.437openalex-snapshot
How Much Knowledge Can You Pack Into the Parameters of a Language Model?
inferredcites →https://doi.org/10.18653/v1/2020.emnlp-main.523openalex-snapshot
LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention
inferredcites →https://doi.org/10.18653/v1/2020.emnlp-main.567openalex-snapshot
SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge
inferredcites →https://doi.org/10.18653/v1/2021.acl-longopenalex-snapshot
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
inferredcites →https://doi.org/10.18653/v1/2021.eacl-mainopenalex-snapshot
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
inferredcites →https://doi.org/10.18653/v1/2021.emnlp-mainopenalex-snapshot
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
inferredcites →https://doi.org/10.18653/v1/2021.findings-acl.61openalex-snapshot
On Commonsense Cues in BERT for Solving Commonsense Tasks
inferredcites →https://doi.org/10.18653/v1/2021.naacl-mainopenalex-snapshot
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
inferredcites →https://doi.org/10.18653/v1/d19-1openalex-snapshot
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
inferredcites →https://doi.org/10.18653/v1/d19-1005openalex-snapshot
Knowledge Enhanced Contextual Word Representations
inferredcites →https://doi.org/10.18653/v1/k17-1openalex-snapshot
Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017)
inferredcites →https://doi.org/10.18653/v1/n18-1202openalex-snapshot
Deep Contextualized Word Representations
inferredcites →https://doi.org/10.18653/v1/p18-1031openalex-snapshot
Universal Language Model Fine-tuning for Text Classification
inferredcites →https://doi.org/10.18653/v1/p19-1139openalex-snapshot
ERNIE: Enhanced Language Representation with Informative Entities
inferredcites →https://doi.org/10.18653/v1/p19-1356openalex-snapshot
What Does BERT Learn about the Structure of Language?
inferredcites →https://doi.org/10.18653/v1/p19-1470openalex-snapshot
COMET: Commonsense Transformers for Automatic Knowledge Graph Construction
inferredcites →https://doi.org/10.18653/v1/p19-1598openalex-snapshot
Barack’s Wife Hillary: Using Knowledge Graphs for Fact-Aware Language Modeling
inferredcites →https://doi.org/10.18653/v1/w19-4828openalex-snapshot
What Does BERT Look at? An Analysis of BERT’s Attention
inferredcites →https://doi.org/10.2307/1419253openalex-snapshot
Nebraska Symposium on Motivation: 1955
inferredcites →https://doi.org/10.3115/v1/d14-1162openalex-snapshot
Glove: Global Vectors for Word Representation
inferredcites →https://doi.org/10.3115/v1/p15-1067openalex-snapshot
Knowledge Graph Embedding via Dynamic Mapping Matrix
inferredcites →https://doi.org/10.48550/arxiv.1310.4546openalex-snapshot
Distributed Representations of Words and Phrases and their Compositionality
inferredcites →https://doi.org/10.48550/arxiv.1906.08237openalex-snapshot
XLNet: Generalized Autoregressive Pretraining for Language Understanding
inferredcites →https://doi.org/10.48550/arxiv.1910.10683openalex-snapshot
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
inferredcites →https://doi.org/10.52202/068431-2704openalex-snapshot
Deep Bidirectional Language-Knowledge Graph Pretraining
inferredcites →https://doi.org/10.5281/zenodo.16880422openalex-snapshot
Spirit In the Shell: A Mathematically Plausible Pathway from Emotions to Metacognition in Artificial Intelligence Systems

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