Author

Youngjoon Jang

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Preprint Sep 2026

RenderRank: Learning to Rerank Text with Compressed Visual Tokens

Rendering document text as images allows vision-language models to encode documents as visual tokens, which can reduce input sequence length compared with text input. This reduction in input length is particularly useful for reranking, where each query involves scoring multiple candidate documents and token savings app...

Seongtae Hong, Youngjoon Jang, Jungseob Lee et al. · 0 citations

Jul 2026

LAMAR: An Open Language-Aware Multilingual Alignment Reranker

This work releases LAMAR, a language aware multilingual cross encoder trained to account for both semantic relevance and language coherence, which achieves the best performance overall and across all languages examined individually on general multilingual reranking benchmarks.

Seongtae Hong, Youngjoon Jang, Jungseob Lee et al. · arXiv.org · 0 citations

Preprint Aug 2026

KoVRE: Training an Efficient Embedding Model for Korean Visual Document Retrieval

KoVRE: Korean Visual Document Retrieval Embedding is introduced, a single-vector retriever for Korean visual documents, alongside a comprehensive training recipe, demonstrating that targeted bilingual supervision and carefully designed training strategies can produce a highly effective Korean VDR model across diverse d...

Yongbin Choi, Gyuho Shim, Youngjoon Jang · 0 citations