activity
20222025
most citedMTEB: Massive Text Embedding Benchmark

69 citations · 176 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CL2025

GemMaroc: Unlocking Darija Proficiency in LLMs with Minimal Data

Abderrahman Skiredj, Ferdaous Azhari, Houdaifa Atou +2

Open-source large language models (LLMs) still marginalise Moroccan Arabic (Darija), forcing practitioners either to bolt on heavyweight Arabic adapters or to sacrifice the very re…

cs.AI2025★ 4 cited

SmolVLM: Redefining small and efficient multimodal models

Andrés Marafioti, Orr Zohar, Miquel Farré +14

Large Vision-Language Models (VLMs) deliver exceptional performance but require significant computational resources, limiting their deployment on mobile and edge devices. Smaller V…

cs.SE2024★ 67 cited

StarCoder 2 and The Stack v2: The Next Generation

Anton Lozhkov, Raymond Li, Loubna Ben Allal +63

The BigCode project, an open-scientific collaboration focused on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder2. In partnership wi…

cs.CL2023★ 1 cited

FinGPT: Large Generative Models for a Small Language

Risto Luukkonen, Ville Komulainen, Jouni Luoma +18

Large language models (LLMs) excel in many tasks in NLP and beyond, but most open models have very limited coverage of smaller languages and LLM work tends to focus on languages wh…

cs.CL2023★ 32 cited

Scaling Data-Constrained Language Models

Niklas Muennighoff, Alexander M. Rush, Boaz Barak +6

The current trend of scaling language models involves increasing both parameter count and training dataset size. Extrapolating this trend suggests that training dataset size may so…

cs.CL2022

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

BigScience Workshop, :, Teven Le Scao +391

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…

cs.CL2022★ 69 cited

MTEB: Massive Text Embedding Benchmark

Niklas Muennighoff, Nouamane Tazi, Loïc Magne +1

Text embeddings are commonly evaluated on a small set of datasets from a single task not covering their possible applications to other tasks. It is unclear whether state-of-the-art…

cs.CL2022★ 3 cited

Masader Plus: A New Interface for Exploring +500 Arabic NLP Datasets

Yousef Altaher, Ali Fadel, Mazen Alotaibi +18

Masader (Alyafeai et al., 2021) created a metadata structure to be used for cataloguing Arabic NLP datasets. However, developing an easy way to explore such a catalogue is a challe…