19 citations · 23 across the 8 of their papers we have counts for
7 papers · 1 filter
Wikidata Search Traces: A Dataset for Training Knowledge Graph Search Agents
Mohamed Chenene, Carlos Rosas-Hinostroza, Pierre-Carl Langlais +2
Wikidata is one of the largest open knowledge bases, yet answering a complex question over it still requires a SPARQL query that names the right entities and properties and chains…
It's All Training: A Fully Synthetic Single-Stage Recipe for LLMs
Pierre-Carl Langlais, Pieter Delobelle, Yannick Detrois +7
Current pre-training datasets are derived from web crawls, with all their issues, and were not designed to support mid- and post-training pipelines--for instance, they contain litt…
Model in Distress: Sentiment Analysis on French Synthetic Social Media
Pierre-Carl Langlais, Pavel Chizhov, Yannick Detrois +4
Automated analysis of customer feedback on social media is hindered by three challenges: the high cost of annotated training data, the scarcity of evaluation sets, especially in mu…
Common Corpus: The Largest Collection of Ethical Data for LLM Pre-Training
Pierre-Carl Langlais, Pavel Chizhov, Catherine Arnett +8
Large Language Models (LLMs) are pre-trained on large amounts of data from different sources and domains. Such datasets often contain trillions of tokens, including large portions…
Even Small Reasoners Should Quote Their Sources: Introducing the Pleias-RAG Model Family
Pierre-Carl Langlais, Pavel Chizhov, Mattia Nee +7
We introduce a new generation of small reasoning models for RAG, search, and source summarization. Pleias-RAG-350m and Pleias-RAG-1B are mid-trained on a large synthetic dataset em…
Who Benchmarks the Benchmarks? Towards Comprehensive Evaluation of Commonsense Reasoning Benchmarks
Pavel Chizhov, Mattia Nee, Anton Changalidis +4
Commonsense reasoning is a key language model capability, as it is purportedly a prerequisite for many basic tasks, unlike specific factual knowledge. It is often measured with mul…
Toxicity of the Commons: Curating Open-Source Pre-Training Data
Catherine Arnett, Eliot Jones, Ivan P. Yamshchikov +1
Open-source large language models are becoming increasingly available and popular among researchers and practitioners. While significant progress has been made on open-weight model…