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Soyeong Jeong

ACL 2026×2检索与知识多模态可解释性推理强化学习与后训练
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一作贡献30
核心/参与5
方向广度10
合作网络6
1 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
作者位次 #3/5ACL 2026Poster· Natural Language Processing

U niversal RAG : Retrieval-Augmented Generation over Corpora of Diverse Modalities and Granularities

Woongyeong Yeo · Kangsan Kim · Soyeong Jeong · Jinheon Baek · Sung Ju Hwang

摘要

Retrieval-Augmented Generation (RAG) has shown substantial promise in improving factual accuracy by grounding model responses with external knowledge relevant to queries. However, most existing approaches are limited to a text-only corpus, and while recent efforts have extended RAG to other modal...

检索与知识多模态可解释性OpenReview 项目页
一作ACL 2026Findings· Findings of ACL

When Thoughts Meet Facts: Reusable Reasoning for Long-Context LM s

Soyeong Jeong · Taehee Jung · Sung Ju Hwang · Joo-Kyung Kim · Dongyeop Kang

摘要

Recent Long-Context Language Models (LCLMs) can process hundreds of thousands of tokens in a single prompt, enabling new opportunities for knowledge-intensive multi-hop reasoning by integrating large sets of retrieved documents or, in some cases, directly all necessary information. However, simpl...

检索与知识推理强化学习与后训练OpenReview 项目页

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