10 papers · 1 filter
RenderRank: Learning to Rerank Text with Compressed Visual Tokens
Seongtae Hong, Youngjoon Jang, Jungseob Lee +2
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 reductio…
LAMAR: An Open Language-Aware Multilingual Alignment Reranker
Seongtae Hong, Youngjoon Jang, Jungseob Lee +2
In multilingual retrieval augmented generation pipelines, an embedding model can retrieve relevant documents written in multiple languages, which are subsequently reranked before a…
Rescaling MLM-Head for Neural Sparse Retrieval
Youngjoon Jang, Seongtae Hong, Jonah Turner +1
Learned sparse retrieval (LSR) models such as SPLADE have traditionally used BERT-style masked language models as backbone encoders. A natural expectation is that replacing BERT wi…
SHIFT: Semantic Harmonization via Index-side Feature Transformation for Multilingual Information Retrieval
Youngjoon Jang, Seongtae Hong, Hyeonseok Moon +1
With the rapid expansion of massive multilingual corpora, Multilingual Information Retrieval (MLIR) has emerged as a critical technology for global information access. MLIR enables…
SemBridge: Language Transfer in Sparse Encoders via Multilingual Semantic Bridges
Seongtae Hong, Youngjoon Jang, Jia-Heui Ju +2
Sparse encoders offer high-precision retrieval by representing term importance within a vocabulary space, yet their English-centric structures pose a critical impediment to languag…
MLAIRE: Multilingual Language-Aware Information Retrieval Evaluation Protocal
Youngjoon Jang, Seongtae Hong, Hyeonseok Moon +1
Multilingual Information Retrieval is increasingly important in real-world search settings, where users issue queries over mixed-language corpora. Existing evaluations mainly rewar…
MIMO: Multilingual Information Retrieval via Monolingual Objectives
Youngjoon Jang, Seongtae Hong, Heuiseok Lim
Multilingual Information Retrieval (MLIR) reflects real-world search environments in which queries and relevant documents may appear in different languages within a mixed-language…
Beyond Hard Negatives: The Importance of Score Distribution in Knowledge Distillation for Dense Retrieval
Youngjoon Jang, Seongtae Hong, Hyeonseok Moon +1
Transferring knowledge from a cross-encoder teacher via Knowledge Distillation (KD) has become a standard paradigm for training retrieval models. While existing studies have largel…
Improving Semantic Proximity in Information Retrieval through Cross-Lingual Alignment
Seongtae Hong, Youngjoon Jang, Jungseob Lee +2
With the increasing accessibility and utilization of multilingual documents, Cross-Lingual Information Retrieval (CLIR) has emerged as an important research area. Conventionally, C…
Improving Korean-English Cross-Lingual Retrieval: A Data-Centric Study of Language Composition and Model Merging
Youngjoon Jang, Junyoung Son, Taemin Lee +5
With the increasing utilization of multilingual text information, Cross-Lingual Information Retrieval (CLIR) has become a crucial research area. However, the impact of training dat…