Papers by Jeongho Yoon
LangSAE Editing: Improving Multilingual Information Retrieval via Post-hoc Language Identity Removal (2026.acl-long)
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| Challenge: | Existing methods for dense retrieval in multilingual environments encode language identity alongside semantics. |
| Approach: | They propose a method that trains on pooled embeddings to remove language-identity signal directly in vector space. |
| Outcome: | The proposed method improves ranking quality and cross-language coverage across multiple languages with especially strong gains for script-distinct languages. |
Towards Privacy-Preserving Large Language Model: Text-free Inference Through Alignment and Adaptation (2026.acl-long)
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| Challenge: | Existing LLMs require users to submit raw text regardless of its sensitivity, resulting in substantial computational overhead and degrade model performance. |
| Approach: | They propose a new training pipeline that allows a client-side encoder to condition on k-pooled prompt embeddings instead of raw text and a server-side projection module to fine-tune the projection module and LLM on private, domain-specific data using noise-injected embeddables. |
| Outcome: | The proposed approach eliminates the need for transmitting raw prompt text while maintaining a favorable balance between privacy preservation and model utility for both clients and service providers. |