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Hyeonseok Moon

ACL 2026×2ICLR 2026SIGIR 2026对齐与偏好检索与知识可解释性效率与系统社会与人本
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1 一作 · 4 篇 · ACL 2026 / ICLR 2026 / SIGIR 2026

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2026 顶会论文

4
作者位次 #4/5ACL 2026Poster· Natural Language Processing

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

Jeongho Yoon · Chanhee Park · Yongchan Chun · Hyeonseok Moon · Heuiseok Lim

摘要

Current LLM-based services typically require users to submit raw text regardless of its sensitivity. While intuitive, such practice introduces substantial privacy risks, as unauthorized access may expose personal, medical, or legal information. Although prior defenses strived to mitigate these ri...

效率与系统社会与人本对齐与偏好OpenReview 项目页
一作ACL 2026Findings· Findings of ACL

N eedle C hain: Measuring Intact Context Comprehension Capability of Large Language Models

Hyeonseok Moon · Heuiseok Lim

摘要

Recent reports suggest that LLMs can handle increasingly long contexts. However, many existing benchmarks for context understanding embed substantial query-irrelevant content, which shifts evaluation toward retrieving relevant snippets rather than fully integrating all provided information. Under...

评测与基准推理检索与知识OpenReview 项目页
作者位次 #3/4SIGIR 2026Poster· Information Retrieval (Short)

Beyond Hard Negatives: The Importance of Score Distribution in Knowledge Distillation

Youngjoon Jang · Seongtae Hong · Hyeonseok Moon · Heuiseok Lim

摘要

Transferring knowledge from a cross-encoder teacher via Knowledge Distillation (KD) has become a standard paradigm for training retrieval models. While existing studies have largely focused on mining hard negatives to improve discrimination, the systematic composition of training data and the res...

检索与知识对齐与偏好强化学习与后训练OpenReview

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