1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2026
Kakugo: Distillation of Low-Resource Languages into Small Language Models
Peter Devine, Mardhiyah Sanni, Farid Adilazuarda +2
We present Kakugo, a novel and cost-effective pipeline designed to train general-purpose Small Language Models (SLMs) for low-resource languages using only the language name as inp…
cs.CL2025
M-IFEval: Multilingual Instruction-Following Evaluation
Antoine Dussolle, Andrea Cardeña Díaz, Shota Sato +1
Instruction following is a core capability of modern Large language models (LLMs), making evaluating this capability essential to understanding these models. The Instruction Follow…
cs.LG2025★ 1 cited
ALoFTRAG: Automatic Local Fine Tuning for Retrieval Augmented Generation
Peter Devine
Retrieval Augmented Generation (RAG) systems have been shown to improve the accuracy of Large Language Model (LLM) outputs. However, these models can often achieve low accuracy whe…