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Arnault Pachot

4 papers hereh-index 476 citations12 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.FL1
  • cs.HC1
  • cs.LG1
  • stat.ML1
same name
  • Arnault Pachot — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedExact Synthetic Populations for Scalable Societal and Market Modeling

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

cs.LG2026

Transparent Screening for LLM Inference and Training Impacts

Arnault Pachot, Thierry Petit

This paper presents a transparent screening framework for estimating inference and training impacts of current large language models under limited observability. The framework conv…

stat.ML2025★ 1 cited

Exact Synthetic Populations for Scalable Societal and Market Modeling

Thierry Petit, Arnault Pachot

We introduce a constraint-programming framework for generating synthetic populations that reproduce target statistics with high precision while enforcing full individual consistenc…

cs.HC2025

Llms, Virtual Users, and Bias: Predicting Any Survey Question Without Human Data

Enzo Sinacola, Arnault Pachot, Thierry Petit

Large Language Models (LLMs) offer a promising alternative to traditional survey methods, potentially enhancing efficiency and reducing costs. In this study, we use LLMs to create…

cs.FL2024

Declarative Integration and Management of Large Language Models through Finite Automata: Application to Automation, Communication, and Ethics

Thierry Petit, Arnault Pachot, Claire Conan-Vrinat +1

This article introduces an innovative architecture designed to declaratively combine Large Language Models (LLMs) with shared histories, and triggers to identify the most appropria…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.