Papers by Seojin Hwang

2 papers
Enhancing Multilingual RAG Systems with Debiased Language Preference-Guided Query Fusion (2026.findings-acl)

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Challenge: Existing studies show that mRAGs exhibit a perceived preference for high-resource languages, particularly English.
Approach: They propose a debiased language preference metric to explicitly factor out structural priors . they propose mRAG framework that leverages monolingual alignment to optimize cross-lingual retrieval and generation.
Outcome: The proposed framework outperforms baselines for English pivoting and mRAG in multiple languages.
Personality Editing for Language Models through Adjusting Self-Referential Queries (2026.eacl-long)

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Challenge: Large Language Models (LLMs) are integral to conversational agents and content creation, but they lack robustness and require large-scale training data to achieve significant improvements in personality alignment.
Approach: They propose a method that introduces adjustment queries where self-referential statements grounded in psychological constructs are treated analogously to factual knowledge to enable direct editing of personality-related responses.
Outcome: The proposed method improves personality alignment across personality dimensions and requires only 12 editing samples to achieve significant improvements.

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