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Geon Lee

KDD 2026×2ACL 2026ICML 2026SIGIR 2026检索与知识评测与基准多模态推理智能体与工具
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一作贡献80
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方向广度19
合作网络9
2 一作 · 5 篇 · KDD 2026 / ACL 2026 / ICML 2026 / SIGIR 2026

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2026 顶会论文

5
一作ICML 2026Poster· Deep Learning / Graph Neural Networks

Rethinking Contrastive Learning for Graph Collaborative Filtering: Limitations and a Simple Remedy

Geon Lee · Sunwoo Kim · Kyungho Kim · Kijung Shin

作者位次 #2/5ACL 2026Findings· Findings of ACL

Hybrid-Vector Retrieval for Visually Rich Documents: Combining Single-Vector Efficiency and Multi-Vector Accuracy

Juyeon Kim · Geon Lee · Dongwon Choi · Taeuk Kim · Kijung Shin

摘要

Retrieval over visually rich documents is essential for tasks such as legal discovery, scientific search, and enterprise knowledge management. Existing approaches fall into two paradigms: single-vector retrieval, which is efficient but coarse, and multi-vector retrieval, which is accurate but com...

检索与知识评测与基准多模态OpenReview 项目页
作者位次 #2/5SIGIR 2026Poster· Information Retrieval (Short)

ItemRAG: Item-Based Retrieval-Augmented Generation for LLM-Based Recommendation

Sunwoo Kim · Geon Lee · Kyungho Kim · Jaemin Yoo · Kijung Shin

摘要

Recently, large language models (LLMs) have been widely used as recommender systems, owing to their reasoning capability and effectiveness in handling cold-start items. A common approach prompts an LLM with a target user's purchase history to recommend items from a candidate set, often enhanced w...

检索与知识推理OpenReview

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