[PDF] Top 20 Contextualized Diachronic Word Representations
Has 10000 "Contextualized Diachronic Word Representations" found on our website. Below are the top 20 most common "Contextualized Diachronic Word Representations".
Contextualized Diachronic Word Representations
... the diachronic word embed- dings for a downstream NLP ...the diachronic word embed- dings can be used as features to build a temporally- aware tweet ... See full document
13
Gender Bias in Contextualized Word Embeddings
... For word representations, Bolukbasi et ...that word embed- dings encode societal biases about gender roles and occupations, ...pretrained word embeddings also reflect this ...on word ... See full document
6
Contextualized Representations for Low resource Utterance Tagging
... In this paper, we adapt the technique of learning contextualized representations using unsupervised pretraining to learn representations for utterances in the context of the dialogue. We first ... See full document
7
CARER: Contextualized Affect Representations for Emotion Recognition
... unique word embeddings and has been proven effective for text ...available word vectors of word2vec, which is common when there are limited computing re- sources, the accuracy keeps dropping at significant ... See full document
11
Low Resource Parsing with Crosslingual Contextualized Representations
... Each pair of related languages shares features like word order, morphology, or script. For exam- ple, Arabic and Hebrew are similar in their rich transfixing morphology (de Lhoneux et al., 2018), and Dutch and ... See full document
12
Retrofitting Contextualized Word Embeddings with Paraphrases
... Contextualized word embedding models, such as ELMo, generate meaningful representations of words and their ...the contextualized embedding of a word changes drastically when the context ... See full document
6
Classification and Clustering of Arguments with Contextualized Word Embeddings
... target word into account. This yields word representations that better match the specific sense of the word in a ...search, contextualized representations need to be able to ... See full document
12
Evaluating the Underlying Gender Bias in Contextualized Word Embeddings
... the word association be- tween man to computer programmer as woman to homemaker (Bolukbasi et ...Pre-trained word embeddings are used in many NLP down- stream tasks, such as natural language inference ... See full document
7
How Contextual are Contextualized Word Representations? Comparing the Geometry of BERT, ELMo, and GPT 2 Embeddings
... ized representations be explained by a static em- bedding, on ...all representations of a single ...a word vector obtained using GloVe, for example, would be similar to the static embedding that ... See full document
11
L2F/INESC ID at SemEval 2019 Task 2: Unsupervised Lexical Semantic Frame Induction using Contextualized Word Representations
... on contextualized embedding representations of the verbs and ar- ...such representations is appro- priate in the context of this task, since they provide cues for word-sense ... See full document
7
Temporal Word Analogies: Identifying Lexical Replacement with Diachronic Word Embeddings
... of word meanings over time using diachronic text corpora is a relatively niche subject with little commercial applicability, it has recently gained attention in the broader compu- tational linguistics ...to ... See full document
6
CX ST RNM at SemEval 2019 Task 3: Fusion of Recurrent Neural Networks Based on Contextualized and Static Word Representations for Contextual Emotion Detection
... and contextualized models used in the proposed method, ...features word representation, and the se- cond one is a baseline model 2-layer BI-LSTM Neural Network as well but is learned on conte- xtualized ... See full document
5
Improving Chemical Named Entity Recognition in Patents with Contextualized Word Embeddings
... alized word representations by combining inter- nal states of different layers in neural language ...models. Contextualized word representation can help to improve performance in various NLP ... See full document
11
SEx BiST: A Multi Source Trainable Parser with Deep Contextualized Lexical Representations
... gual word embeddings (Ruder et ...one word embedding on top of the other to make both representations share the same seman- tic space (Artetxe et ...bilingual word embed- dings from bilingual ... See full document
10
Exploring Diachronic Changes of Biomedical Knowledge using Distributed Concept Representations
... Another popular method to represent words are distributed representations. Words are repre- sented in a dense and continuous form, that en- ables us to capture the meaning in a condensed form. There are various ... See full document
11
Extending a Parser to Distant Domains Using a Few Dozen Partially Annotated Examples
... In this work, we focus on the direct impact that just a few dozen partially annotated out-of-domain examples can have, when using a particular neural model with contextualized word representations. ... See full document
10
Low Resource Sequence Labeling via Unsupervised Multilingual Contextualized Representations
... In our experiments, we set the hidden size of word- level LSTM and character-level LSTM to be 300 and 100, respectively. The character embedding size is set to be 100. We apply dropout at both the input and the ... See full document
12
Tracing armed conflicts with diachronic word embedding models
... mantic representations of country names) certainly presupposes cultural shifts in the associations for these country names (not a real change of dictio- nary ... See full document
6
Improved Word Sense Disambiguation Using Pre Trained Contextualized Word Representations
... a word given its surrounding ...a word in a ...target word em- ...next word in the for- ward LSTM and the previous word in the back- ward ... See full document
10
Deep contextualized word representations for detecting sarcasm and irony
... each word-level embedding contains con- textual information from their ...Billion Word Benchmark which contains about 800M tokens of news crawl data from WMT 2011 (Chelba et ... See full document
6
Related subjects