Myeongjun Jang

According to our database, Myeongjun Jang authored at least 18 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Consistency Analysis of ChatGPT.

Myeongjun Jang, Thomas Lukasiewicz

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Improving Language Models' Meaning Understanding and Consistency by Learning Conceptual Roles from Dictionary.

Myeongjun Jang, Thomas Lukasiewicz

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

KNOW How to Make Up Your Mind! Adversarially Detecting and Alleviating Inconsistencies in Natural Language Explanations.

Myeongjun Jang, Bodhisattwa Prasad Majumder, Julian J. McAuley, Thomas Lukasiewicz, Oana-Maria Camburu

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

2022

NoiER: An Approach for Training More Reliable Fine-Tuned Downstream Task Models.

Myeongjun Jang, Thomas Lukasiewicz

IEEE ACM Trans. Audio Speech Lang. Process., 2022

Sentence transition matrix: An efficient approach that preserves sentence semantics.

Myeongjun Jang, Pilsung Kang

Comput. Speech Lang., 2022

KOBEST: Korean Balanced Evaluation of Significant Tasks.

Dohyeong Kim, Myeongjun Jang, Deuk Sin Kwon, Eric Davis

CoRR, 2022

Beyond Distributional Hypothesis: Let Language Models Learn Meaning-Text Correspondence.

Myeongjun Jang, Frank Mtumbuka, Thomas Lukasiewicz

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

BECEL: Benchmark for Consistency Evaluation of Language Models.

Myeongjun Jang, Deuk Sin Kwon, Thomas Lukasiewicz

Proceedings of the 29th International Conference on Computational Linguistics, 2022

KoBEST: Korean Balanced Evaluation of Significant Tasks.

Myeongjun Jang, Dohyung Kim, Deuk Sin Kwon, Eric Davis

Proceedings of the 29th International Conference on Computational Linguistics, 2022

2021

Are Training Resources Insufficient? Predict First Then Explain!

Myeongjun Jang, Thomas Lukasiewicz

CoRR, 2021

NoiER: An Approach for Training more Reliable Fine-TunedDownstream Task Models.

Myeongjun Jang, Thomas Lukasiewicz

CoRR, 2021

Accurate, yet inconsistent? Consistency Analysis on Language Understanding Models.

Myeongjun Jang, Deuk Sin Kwon, Thomas Lukasiewicz

CoRR, 2021

Intrusion Detection Based on Sequential Information Preserving Log Embedding Methods and Anomaly Detection Algorithms.

CzangYeob Kim, Myeongjun Jang, Seungwan Seo, Kyeongchan Park, Pilsung Kang

IEEE Access, 2021

Learning-Free Unsupervised Extractive Summarization Model.

Myeongjun Jang, Pilsung Kang

IEEE Access, 2021

2020

Corrigendum to "Recurrent neural network-based semantic variational autoencoder for Sequence-to-sequence learning" [Information Sciences 490 (2019) 59-73].

Myeongjun Jang, Seungwan Seo, Pilsung Kang

Inf. Sci., 2020

Paraphrase thought: Sentence embedding module imitating human language recognition.

Myeongjun Jang, Pilsung Kang

Inf. Sci., 2020

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

Seungwan Seo, Deokseong Seo, Myeongjun Jang, Jaeyun Jeong, Pilsung Kang

Expert Syst. Appl., 2020

2019

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

Myeongjun Jang, Seungwan Seo, Pilsung Kang

Inf. Sci., 2019