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Home/Authors/Heuiseok Lim

Heuiseok Lim

4 indexed papers

Recent (6 mo)
4
With code
0
Influential cites
0
Benchmarked
0

Publications per year

4
26

Top categories

AI×4Info Retrieval×2NLP×1Crypto×1

Frequent co-authors

Sugyeong Eo1×
Youngjoon Jang1×
Seongtae Hong1×
Joongmin Shin1×
Gyuho Shim1×
Jeongbae Park1×

Research Timeline

2026
Towards Privacy-Preserving Large Language Model: Text-free Inference Through Alignment and Adaptation

The paper introduces Privacy-Preserving Fine-Tuning (PPFT), a novel two-stage pipeline that allows LLMs to process sensitive data via pooled embeddings rather than raw text, achieving a strong balance between privacy and model performance.

HiKEY: Hierarchical Multimodal Retrieval for Open-Domain Document Question Answering

HiKEY proposes a hierarchical, tree-based multimodal retrieval framework that significantly improves open-domain document question answering by addressing document routing and evidence fragmentation.

MIMO: Multilingual Information Retrieval via Monolingual Objectives

The paper proposes MIMO, a two-stage framework that improves Multilingual Information Retrieval (MLIR) by stabilizing cross-lingual alignment and enhancing retrieval discrimination using a combination of knowledge distillation and joint contrastive learning.

Unveiling the Limits of Large Language Models in Inferring Pragmatic Meaning from Non-Verbal Responses

This paper systematically evaluates LLMs' ability to infer pragmatic meaning from non-verbal responses, finding that their accuracy significantly drops compared to verbal inputs.

Highlighted terms show continued research focus across papers

Papers

cs.CLcs.AIRecentJun 1, 2026

Unveiling the Limits of Large Language Models in Inferring Pragmatic Meaning from Non-Verbal Responses

Sugyeong Eo, Heuiseok Lim

This paper systematically evaluates LLMs' ability to infer pragmatic meaning from non-verbal responses, finding that their accuracy significantly drops compared to verbal inputs.

View →
cs.IRcs.AIRecentMay 29, 2026

MIMO: Multilingual Information Retrieval via Monolingual Objectives

Youngjoon Jang, Seongtae Hong, Heuiseok Lim

The paper proposes MIMO, a two-stage framework that improves Multilingual Information Retrieval (MLIR) by stabilizing cross-lingual alignment and enhancing retrieval discrimination using a combination…

View →
cs.AIcs.IRRecentMay 28, 2026

HiKEY: Hierarchical Multimodal Retrieval for Open-Domain Document Question Answering

Joongmin Shin, Gyuho Shim, Jeongbae Park, Jaehyung Seo +1 more

HiKEY proposes a hierarchical, tree-based multimodal retrieval framework that significantly improves open-domain document question answering by addressing document routing and evidence fragmentation.

View →
cs.CRcs.AIRecentApr 8, 2026

Towards Privacy-Preserving Large Language Model: Text-free Inference Through Alignment and Adaptation

Jeongho Yoon, Chanhee Park, Yongchan Chun, Hyeonseok Moon +1 more

The paper introduces Privacy-Preserving Fine-Tuning (PPFT), a novel two-stage pipeline that allows LLMs to process sensitive data via pooled embeddings rather than raw text, achieving a strong balance…

View →