Evolution of semantic similarity—a survey
D Chandrasekaran, V Mago - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
Estimating the semantic similarity between text data is one of the challenging and open
research problems in the field of Natural Language Processing (NLP). The versatility of …
research problems in the field of Natural Language Processing (NLP). The versatility of …
Analysis methods in neural language processing: A survey
Y Belinkov, J Glass - … of the Association for Computational Linguistics, 2019 - direct.mit.edu
The field of natural language processing has seen impressive progress in recent years, with
neural network models replacing many of the traditional systems. A plethora of new models …
neural network models replacing many of the traditional systems. A plethora of new models …
How contextual are contextualized word representations? Comparing the geometry of BERT, ELMo, and GPT-2 embeddings
K Ethayarajh - arXiv preprint arXiv:1909.00512, 2019 - arxiv.org
Replacing static word embeddings with contextualized word representations has yielded
significant improvements on many NLP tasks. However, just how contextual are the …
significant improvements on many NLP tasks. However, just how contextual are the …
Is bert really robust? a strong baseline for natural language attack on text classification and entailment
Abstract Machine learning algorithms are often vulnerable to adversarial examples that have
imperceptible alterations from the original counterparts but can fool the state-of-the-art …
imperceptible alterations from the original counterparts but can fool the state-of-the-art …
Language models as knowledge bases?
Recent progress in pretraining language models on large textual corpora led to a surge of
improvements for downstream NLP tasks. Whilst learning linguistic knowledge, these …
improvements for downstream NLP tasks. Whilst learning linguistic knowledge, these …
Probing pretrained language models for lexical semantics
The success of large pretrained language models (LMs) such as BERT and RoBERTa has
sparked interest in probing their representations, in order to unveil what types of knowledge …
sparked interest in probing their representations, in order to unveil what types of knowledge …
Null it out: Guarding protected attributes by iterative nullspace projection
The ability to control for the kinds of information encoded in neural representation has a
variety of use cases, especially in light of the challenge of interpreting these models. We …
variety of use cases, especially in light of the challenge of interpreting these models. We …
Senteval: An evaluation toolkit for universal sentence representations
We introduce SentEval, a toolkit for evaluating the quality of universal sentence
representations. SentEval encompasses a variety of tasks, including binary and multi-class …
representations. SentEval encompasses a variety of tasks, including binary and multi-class …
WiC: the word-in-context dataset for evaluating context-sensitive meaning representations
MT Pilehvar, J Camacho-Collados - arXiv preprint arXiv:1808.09121, 2018 - arxiv.org
By design, word embeddings are unable to model the dynamic nature of words' semantics,
ie, the property of words to correspond to potentially different meanings. To address this …
ie, the property of words to correspond to potentially different meanings. To address this …
Evaluating word embedding models: Methods and experimental results
Extensive evaluation on a large number of word embedding models for language
processing applications is conducted in this work. First, we introduce popular word …
processing applications is conducted in this work. First, we introduce popular word …