7 papers · 1 filter
Steering LLMs toward Korean Local Speech: Iterative Refinement Framework for Faithful Dialect Translation
Keunhyeung Park, Seunguk Yu, Youngbin Kim
Standard-to-dialect machine translation remains challenging due to a persistent dialect gap in large language models and evaluation distortions inherent in n-gram metrics, which fa…
Medal Matters: Probing LLMs' Failure Cases Through Olympic Rankings
Juhwan Choi, Seunguk Yu, JungMin Yun +1
Large language models (LLMs) have achieved remarkable success in natural language processing tasks, yet their internal knowledge structures remain poorly understood. This study exa…
LLM Agents at the Roundtable: A Multi-Perspective and Dialectical Reasoning Framework for Essay Scoring
Jinhee Jang, Ayoung Moon, Minkyoung Jung +2
The emergence of large language models (LLMs) has brought a new paradigm to automated essay scoring (AES), a long-standing and practical application of natural language processing…
From Ground Trust to Truth: Disparities in Offensive Language Judgments on Contemporary Korean Political Discourse
Seunguk Yu, Jungmin Yun, Jinhee Jang +1
Although offensive language continually evolves over time, even recent studies using LLMs have predominantly relied on outdated datasets and rarely evaluated the generalization abi…
Delving into Multilingual Ethical Bias: The MSQAD with Statistical Hypothesis Tests for Large Language Models
Seunguk Yu, Juhwan Choi, Youngbin Kim
Despite the recent strides in large language models, studies have underscored the existence of social biases within these systems. In this paper, we delve into the validation and c…
Beyond Single-User Dialogue: Assessing Multi-User Dialogue State Tracking Capabilities of Large Language Models
Sangmin Song, Juhwan Choi, JungMin Yun +1
Large language models (LLMs) have demonstrated remarkable performance in zero-shot dialogue state tracking (DST), reducing the need for task-specific training. However, conventiona…