collaborators

7 papers

cs.CL2025

Apertus: Democratizing Open and Compliant LLMs for Global Language Environments

Project Apertus, Alejandro Hernández-Cano, Alexander Hägele +100

We present Apertus, a fully open suite of large language models (LLMs) designed to address two systemic shortcomings in today's open model ecosystem: data compliance and multilingu…

cs.LG2025

Hybrid Decentralized Optimization: Leveraging Both First- and Zeroth-Order Optimizers for Faster Convergence

Matin Ansaripour, Shayan Talaei, Giorgi Nadiradze +1

Distributed optimization is the standard way of speeding up machine learning training, and most of the research in the area focuses on distributed first-order, gradient-based metho…

cs.CL2025

Can Performant LLMs Be Ethical? Quantifying the Impact of Web Crawling Opt-Outs

Dongyang Fan, Vinko Sabolčec, Matin Ansaripour +4

The increasing adoption of web crawling opt-outs by copyright holders of online content raises critical questions about the impact of data compliance on large language model (LLM)…

cs.CL2025

WikiMixQA: A Multimodal Benchmark for Question Answering over Tables and Charts

Negar Foroutan, Angelika Romanou, Matin Ansaripour +3

Documents are fundamental to preserving and disseminating information, often incorporating complex layouts, tables, and charts that pose significant challenges for automatic docume…

cs.GT2024

Approximate EFX and Exact tEFX Allocations for Indivisible Chores: Improved Algorithms

Mahyar Afshinmehr, Matin Ansaripour, Alireza Danaei +1

We explore the fair distribution of a set of indivisible chores among agents, where each agent's costs are evaluated using a monotone cost function. Our focus lies on two f…

cs.AI2024

LLaMa-SciQ: An Educational Chatbot for Answering Science MCQ

Marc-Antoine Allard, Matin Ansaripour, Maria Yuffa +1

Large Language Models (LLMs) often struggle with tasks requiring mathematical reasoning, particularly multiple-choice questions (MCQs). To address this issue, we developed LLaMa-Sc…