5 papers
TERMINATOR: Learning Optimal Exit Points for Early Stopping in Chain-of-Thought Reasoning
Alliot Nagle, Jakhongir Saydaliev, Dhia Garbaya +3
Large Reasoning Models (LRMs) achieve impressive performance on complex reasoning tasks via Chain-of-Thought (CoT) reasoning, which enables them to generate intermediate thinking t…
CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data
Pedro Ortiz Suarez, Laurie Burchell, Catherine Arnett +94
Language identification (LID) is a fundamental step in curating multilingual corpora. However, LID models still perform poorly for many languages, especially on the noisy and heter…
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…
ConLID: Supervised Contrastive Learning for Low-Resource Language Identification
Negar Foroutan, Jakhongir Saydaliev, Ye Eun Kim +1
Language identification (LID) is a critical step in curating multilingual LLM pretraining corpora from web crawls. While many studies on LID model training focus on collecting dive…
LLM Agents for Interactive Exploration of Historical Cadastre Data: Framework and Application to Venice
Tristan Karch, Jakhongir Saydaliev, Isabella Di Lenardo +1
Cadastral data reveal key information about the historical organization of cities but are often non-standardized due to diverse formats and human annotations, complicating large-sc…