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Hyeju Jang

3 accepted papers

2025

Large Language Models Are Better Logical Fallacy Reasoners with Counterargument, Explanation, and Goal-Aware Prompt Formulation

NAACL 2025findings

The advancement of Large Language Models (LLMs) has greatly improved our ability to process complex language. However, accurately detecting logical fallacies remains a significant challenge. This study presents a novel and effective prompt formulation approach for logical fallacy detection, applicab…

2024

Improving Multi-hop Logical Reasoning in Knowledge Graphs with Context-Aware Query Representation Learning

ACL 2024findings

Multi-hop logical reasoning on knowledge graphs is a pivotal task in natural language processing, with numerous approaches aiming to answer First-Order Logic (FOL) queries. Recent geometry (e.g., box, cone) and probability (e.g., beta distribution)-based methodologies have effectively addressed comp…

2021

T3-Vis: visual analytic for Training and fine-Tuning Transformers in NLP

EMNLP 2021system demonstrations

Transformers are the dominant architecture in NLP, but their training and fine-tuning is still very challenging. In this paper, we present the design and implementation of a visual analytic framework for assisting researchers in such process, by providing them with valuable insights about the model’…