User profiles for Myeongjun Jang
Myeongjun Erik JangUniversity of Oxford Verified email at cs.ox.ac.uk Cited by 234 |
Recurrent neural network-based semantic variational autoencoder for sequence-to-sequence learning
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 …
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 …
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
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 …
explanations (NLEs) generated by a model to justify its predictions, there is very limited …
BECEL: Benchmark for consistency evaluation of language models
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 …
like humans. Despite its importance, however, there is little consensus on the definition …
Kobest: Korean balanced evaluation of significant tasks
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 …
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
Previous methods for system intrusion detection have mainly consisted of those based on
pattern matching that employs prior knowledge extracted from experts' domain knowledge. …
pattern matching that employs prior knowledge extracted from experts' domain knowledge. …
Learning-free unsupervised extractive summarization model
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 …
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
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 …
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
The logical negation property (LNP), which implies generating different predictions for
semantically opposite inputs, is an important property that a trustworthy language model must …
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
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, …
responses against cancer cells and pathogens, while maintaining tolerance against self-antigens, …