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The Dark Side of the Language: Pre-trained Transformers in the DarkNet ...
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Discontinuous Constituency and BERT: A Case Study of Dutch ...
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Cross-Platform Difference in Facebook and Text Messages Language Use: Illustrated by Depression Diagnosis ...
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Improving Word Translation via Two-Stage Contrastive Learning ...
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nigam@COLIEE-22: Legal Case Retrieval and Entailment using Cascading of Lexical and Semantic-based models ...
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Learning grammar with a divide-and-concur neural network ...
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Self-Supervised Representation Learning for Speech Using Visual Grounding and Masked Language Modeling ...
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Accurate Online Posterior Alignments for Principled Lexically-Constrained Decoding ...
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89 |
Introducing Neural Bag of Whole-Words with ColBERTer: Contextualized Late Interactions using Enhanced Reduction ...
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Improving Time Sensitivity for Question Answering over Temporal Knowledge Graphs ...
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HistBERT: A Pre-trained Language Model for Diachronic Lexical Semantic Analysis ...
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Abstract:
Contextualized word embeddings have demonstrated state-of-the-art performance in various natural language processing tasks including those that concern historical semantic change. However, language models such as BERT was trained primarily on contemporary corpus data. To investigate whether training on historical corpus data improves diachronic semantic analysis, we present a pre-trained BERT-based language model, HistBERT, trained on the balanced Corpus of Historical American English. We examine the effectiveness of our approach by comparing the performance of the original BERT and that of HistBERT, and we report promising results in word similarity and semantic shift analysis. Our work suggests that the effectiveness of contextual embeddings in diachronic semantic analysis is dependent on the temporal profile of the input text and care should be taken in applying this methodology to study historical semantic change. ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
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URL: https://dx.doi.org/10.48550/arxiv.2202.03612 https://arxiv.org/abs/2202.03612
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Towards Explainable Evaluation Metrics for Natural Language Generation ...
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ASL Video Corpora & Sign Bank: Resources Available through the American Sign Language Linguistic Research Project (ASLLRP) ...
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How do lexical semantics affect translation? An empirical study ...
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How Effective is Incongruity? Implications for Code-mix Sarcasm Detection ...
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Learning Meta Word Embeddings by Unsupervised Weighted Concatenation of Source Embeddings ...
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COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics ...
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LaPraDoR: Unsupervised Pretrained Dense Retriever for Zero-Shot Text Retrieval ...
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