Recurrent neural network-based semantic variational autoencoder for Sequence-to-sequence learning. - Myeongjun Jang 001; Seungwan Seo; Pilsung Kang 001 (Inf. Sci., 2019)

Unusual customer response identification and visualization based on text mining and anomaly detection. - Seungwan Seo; Deokseong Seo; Myeongjun Jang 001; Jaeyun Jeong; Pilsung Kang 001 (Expert Syst. Appl., 2020)

Paraphrase thought: Sentence embedding module imitating human language recognition. - Myeongjun Jang 001; Pilsung Kang 001 (Inf. Sci., 2020)

Corrigendum to "Recurrent neural network-based semantic variational autoencoder for Sequence-to-sequence learning" [Information Sciences 490 (2019) 59-73]. - Myeongjun Jang 001; Seungwan Seo; Pilsung Kang 001 (Inf. Sci., 2020)

Learning-Free Unsupervised Extractive Summarization Model. - Myeongjun Jang 001; Pilsung Kang 001 (IEEE Access, 2021)

Intrusion Detection Based on Sequential Information Preserving Log Embedding Methods and Anomaly Detection Algorithms. - CzangYeob Kim; Myeongjun Jang 001; Seungwan Seo; Kyeongchan Park; Pilsung Kang 001 (IEEE Access, 2021)

Accurate, yet inconsistent? Consistency Analysis on Language Understanding Models. - Myeongjun Jang 001; Deuk Sin Kwon; Thomas Lukasiewicz (CoRR, 2021)

NoiER: An Approach for Training more Reliable Fine-TunedDownstream Task Models. - Myeongjun Jang 001; Thomas Lukasiewicz (CoRR, 2021)

Are Training Resources Insufficient? Predict First Then Explain! - Myeongjun Jang 001; Thomas Lukasiewicz (CoRR, 2021)

KoBEST: Korean Balanced Evaluation of Significant Tasks. - Myeongjun Jang 001; Dohyung Kim; Deuk Sin Kwon; Eric Davis (COLING, 2022)

BECEL: Benchmark for Consistency Evaluation of Language Models. - Myeongjun Jang 001; Deuk Sin Kwon; Thomas Lukasiewicz (COLING, 2022)

Beyond Distributional Hypothesis: Let Language Models Learn Meaning-Text Correspondence. - Myeongjun Jang 001; Frank Mtumbuka; Thomas Lukasiewicz (NAACL-HLT (Findings), 2022)

KOBEST: Korean Balanced Evaluation of Significant Tasks. - Dohyeong Kim; Myeongjun Jang 001; Deuk Sin Kwon; Eric Davis (CoRR, 2022)

Sentence transition matrix: An efficient approach that preserves sentence semantics. - Myeongjun Jang 001; Pilsung Kang 001 (Comput. Speech Lang., 2022)

NoiER: An Approach for Training More Reliable Fine-Tuned Downstream Task Models. - Myeongjun Jang 001; Thomas Lukasiewicz (IEEE ACM Trans. Audio Speech Lang. Process., 2022)

KNOW How to Make Up Your Mind! Adversarially Detecting and Alleviating Inconsistencies in Natural Language Explanations. - Myeongjun Jang 001; Bodhisattwa Prasad Majumder; Julian J. McAuley; Thomas Lukasiewicz; Oana-Maria Camburu (ACL (2), 2023)

Improving Language Models' Meaning Understanding and Consistency by Learning Conceptual Roles from Dictionary. - Myeongjun Jang 001; Thomas Lukasiewicz (EMNLP, 2023)

Consistency Analysis of ChatGPT. - Myeongjun Jang 001; Thomas Lukasiewicz (EMNLP, 2023)

DriftWatch: A Tool that Automatically Detects Data Drift and Extracts Representative Examples Affected by Drift. - Myeongjun Jang 001; Antonios Georgiadis; Yiyun Zhao; Fran Silavong (NAACL (Industry Track), 2024)

Leveraging Natural Language Processing and Large Language Models for Assisting Due Diligence in the Legal Domain. - Myeongjun Jang 001; Gábor Stikkel (NAACL (Industry Track), 2024)

Pre-training and diagnosing knowledge base completion models. - Vid Kocijan; Myeongjun Erik Jang; Thomas Lukasiewicz (Artif. Intell., 2024)

InstaJudge: Aligning Judgment Bias of LLM-as-Judge with Humans in Industry Applications. - Myeongjun Erik Jang; Fran Silavong (EMNLP (Industry Track), 2025)

Industry-Aligned Granular Topic Modeling. - Sae Young Moon; Myeongjun Erik Jang; Haoyan Luo; Chunyang Xiao; Antonios Georgiadis; Fran Silavong (CoRR, 2026)