User profiles for Myeongjun Jang

Myeongjun Erik Jang

University of Oxford
Verified email at cs.ox.ac.uk
Cited by 234

Recurrent neural network-based semantic variational autoencoder for sequence-to-sequence learning

M Jang, S Seo, P Kang - Information Sciences, 2019 - Elsevier
Sequence-to-sequence (Seq2seq) models have played an important role in the recent
success of various natural language processing methods, such as machine translation, text …

Consistency analysis of chatgpt

ME Jang, T Lukasiewicz - arXiv preprint arXiv:2303.06273, 2023 - arxiv.org
ChatGPT has gained a huge popularity since its introduction. Its positive aspects have been
reported through many media platforms, and some analyses even showed that ChatGPT …

KNOW how to make up your mind! adversarially detecting and alleviating inconsistencies in natural language explanations

M Jang, BP Majumder, J McAuley… - arXiv preprint arXiv …, 2023 - arxiv.org
While recent works have been considerably improving the quality of the natural language
explanations (NLEs) generated by a model to justify its predictions, there is very limited …

BECEL: Benchmark for consistency evaluation of language models

M Jang, DS Kwon, T Lukasiewicz - Proceedings of the 29th …, 2022 - aclanthology.org
Behavioural consistency is a critical condition for a language model (LM) to become trustworthy
like humans. Despite its importance, however, there is little consensus on the definition …

Kobest: Korean balanced evaluation of significant tasks

M Jang, D Kim, DS Kwon, E Davis - Proceedings of the 29th …, 2022 - aclanthology.org
A well-formulated benchmark plays a critical role in spurring advancements in the natural
language processing (NLP) field, as it allows objective and precise evaluation of diverse …

Intrusion detection based on sequential information preserving log embedding methods and anomaly detection algorithms

C Kim, M Jang, S Seo, K Park, P Kang - IEEE Access, 2021 - ieeexplore.ieee.org
Previous methods for system intrusion detection have mainly consisted of those based on
pattern matching that employs prior knowledge extracted from experts' domain knowledge. …

Learning-free unsupervised extractive summarization model

M Jang, P Kang - IEEE Access, 2021 - ieeexplore.ieee.org
Text summarization is an information condensation technique that abbreviates a source
document to a few representative sentences with the intention to create a coherent summary …

Unusual customer response identification and visualization based on text mining and anomaly detection

S Seo, D Seo, M Jang, J Jeong, P Kang - Expert Systems with Applications, 2020 - Elsevier
The Vehicle Dependability Study (VDS) is a survey study on customer satisfaction for
vehicles that have been sold for three years. VDS data analytics plays an important role in the …

Beyond distributional hypothesis: Let language models learn meaning-text correspondence

M Jang, F Mtumbuka, T Lukasiewicz - arXiv preprint arXiv:2205.03815, 2022 - arxiv.org
The logical negation property (LNP), which implies generating different predictions for
semantically opposite inputs, is an important property that a trustworthy language model must …

[HTML][HTML] A robust deep learning workflow to predict CD8+ T-cell epitopes

CH Lee, J Huh, PR Buckley, M Jang, MP Pinho… - Genome Medicine, 2023 - Springer
Background T-cells play a crucial role in the adaptive immune system by triggering
responses against cancer cells and pathogens, while maintaining tolerance against self-antigens, …