1 citations · 1 across the 5 of their papers we have counts for
Showing 2025Show all
3 papers · 1 filter
cs.IR2025
Fantastic (small) Retrievers and How to Train Them: mxbai-edge-colbert-v0 Tech Report
Rikiya Takehi, Benjamin Clavié, Sean Lee +1
In this work, we introduce mxbai-edge-colbert-v0 models, at two different parameter counts: 17M and 32M. As part of our research, we conduct numerous experiments to improve retriev…
cs.IR2025
Simple Projection Variants Improve ColBERT Performance
Benjamin Clavié, Sean Lee, Rikiya Takehi +2
Multi-vector dense retrieval methods like ColBERT systematically use a single-layer linear projection to reduce the dimensionality of individual vectors. In this study, we explore…
cs.IR2025
ProRank: Prompt Warmup via Reinforcement Learning for Small Language Models Reranking
Xianming Li, Aamir Shakir, Rui Huang +4
Reranking is fundamental to information retrieval and retrieval-augmented generation, with recent Large Language Models (LLMs) significantly advancing reranking quality. Most curre…