3 papers
cs.IR2026
ReinPool: Reinforcement Learning Pooling Multi-Vector Embeddings for Retrieval System
Sungguk Cha, DongWook Kim, Mintae Kim +3
Multi-vector embedding models have emerged as a powerful paradigm for document retrieval, preserving fine-grained visual and textual details through token-level representations. Ho…
cs.CV2025
Annotation-Free Reinforcement Learning Query Rewriting via Verifiable Search Reward
Sungguk Cha, DongWook Kim, Taeseung Hahn +3
Optimizing queries for Retrieval-Augmented Generation (RAG) systems poses a significant challenge, particularly across diverse modal indices. We introduce RL-QR, a novel annotation…
cs.CL2025
ixi-GEN: Efficient Industrial sLLMs through Domain Adaptive Continual Pretraining
Seonwu Kim, Yohan Na, Kihun Kim +7
The emergence of open-source large language models (LLMs) has expanded opportunities for enterprise applications; however, many organizations still lack the infrastructure to deplo…