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Minseok Choi

7 accepted papers

2026

ExpGuard: LLM Content Moderation in Specialized Domains

ICLR 2026poster

With the growing deployment of large language models (LLMs) in real-world applications, establishing robust safety guardrails to moderate their inputs and outputs has become essential to ensure adherence to safety policies. Current guardrail models predominantly address general human-LLM interaction…

Cited by 0SourcecodeScholar
2025

Opt-Out: Investigating Entity-Level Unlearning for Large Language Models via Optimal Transport

ACL 2025long

Instruction-following large language models (LLMs), such as ChatGPT, have become widely popular among everyday users. However, these models inadvertently disclose private, sensitive information to their users, underscoring the need for machine unlearning techniques to remove selective information fr…

Cited by 0SourcePDFScholar
2024

Cross-Lingual Unlearning of Selective Knowledge in Multilingual Language Models

EMNLP 2024finding

Pretrained language models memorize vast amounts of information, including private and copyrighted data, raising significant safety concerns. Retraining these models after excluding sensitive data is prohibitively expensive, making machine unlearning a viable, cost-effective alternative. Previous re…

2023

HistRED: A Historical Document-Level Relation Extraction Dataset

ACL 2023long

Despite the extensive applications of relation extraction (RE) tasks in various domains, little has been explored in the historical context, which contains promising data across hundreds and thousands of years. To promote the historical RE research, we present HistRED constructed from Yeonhaengnok.…

2023

SimCKP: Simple Contrastive Learning of Keyphrase Representations

EMNLP 2023long findings

Keyphrase generation (KG) aims to generate a set of summarizing words or phrases given a source document, while keyphrase extraction (KE) aims to identify them from the text. Because the search space is much smaller in KE, it is often combined with KG to predict keyphrases that may or may not exist…

Cited by 0SourcecodeScholar
2022

Rethinking Style Transformer with Energy-based Interpretation: Adversarial Unsupervised Style Transfer using a Pretrained Model

EMNLP 2022main

Style control, content preservation, and fluency determine the quality of text style transfer models. To train on a nonparallel corpus, several existing approaches aim to deceive the style discriminator with an adversarial loss. However, adversarial training significantly degrades fluency compared t…

Cited by 0SourcePDFScholar
2021

Sageflow: Robust Federated Learning against Both Stragglers and Adversaries

NeurIPS 2021poster

While federated learning (FL) allows efficient model training with local data at edge devices, among major issues still to be resolved are: slow devices known as stragglers and malicious attacks launched by adversaries. While the presence of both of these issues raises serious concerns in practica…

Cited by 126SourcePDFScholar