Stage Case-Based Reasoning on Concepts for Sensible Explainable AI- Saclay-H/F

**Description du poste** ------------------------ ### **Domaine** Sciences pour l'ingénieur ### **Contrat** Stage ### **Intitulé de l'offre** Stage Case-Based Reasoning on Concepts for Sensible Explainable AI- Saclay-H/F ### **Sujet de stage** Case-based reasoning is a popular framework for explainable AI. It exposes the network decision process by relating inference-time inputs with prototypes. Recent work proposed to rely on the formalism of Abductive Explanations as to guarantee that an prototype-based explanation is both minimal and sufficient. Assigning meaning to prototypes is however a time-consuming task, as the various models tend to learn prototypes that do not carry sufficiently high-level meaning. A parallel line of work is that of Concept Learning. By injecting concepts meaningful to human operators, Concept Bottleneck Models provide a principled way to map feature maps to annotated concepts, providing an easy to understand - and contest - decision procedure. Recent work display a renewed interest in those approaches, by exposing counterfactuals generation capabilities. ### **Durée du contrat (en mois)** 4 à 6 mois ### **Description de l'offre** As an intern at the CEA, you will have the opportunity to work in a world-renowned research environment. Our teams consist of passionate and dedicated experts, providing an environment conducive to learning and collaboration. You will have access to state-of-the-art equipment and top-tier research resources to carry out your assignments. The work performed may potentially lead to a scientific publication. **Context :** The main objective of the internship is to investigate, design and implement an abductive explanations and concept-based decision procedure. **What do we expect from you ?** The broad internship goals are: * familiarization with the state-of-the-art; * sketching a decision procedure on paper; * implement a proof-of-concept of concept bottleneck models in the CaBRNet library; * evaluate the approach on existing metrics and various human-in-the-loop evaluation methods. #*Cea List* ### **Moyens / Méthodes / Logiciels** CaBRNet ### **Profil du candidat** **Profile :** ##### **Minimal qualifications** * master student or equivalent (2nd/3rd engineering school year) in computer science and/or machine learning; * some knowledge of the Python programming language; * ability to work in a team; ##### **Preferred** * knowledge of the PyTorch framework; * used to work with version control systems (git) and software forges (GitLab); * background on explainable AI; **Localisation du poste** ------------------------- ### **Site** Saclay ### **Localisation du poste** France, Ile-de-France, Essonne (91) ### **Ville** Saclay **Critères candidat** --------------------- ### **Langues** * Français (Courant) * Anglais (Courant) ### **Diplôme préparé** Bac+5 - Master of Science ### **Formation recommandée** Machine Learning ### **Possibilité de poursuite en thèse** Oui **Demandeur** ------------- ### **Disponibilité du poste** 01/03/2027 **Informations générales** -------------------------- ### **Entité de rattachement** Le CEA est un acteur majeur de la recherche, au service des citoyens, de l'économie et de l'Etat. Il apporte des solutions concrètes à leurs besoins dans quatre domaines principaux : transition énergétique, transition numérique, technologies pour la médecine du futur, défense et sécurité sur un socle de recherche fondamentale. Le CEA s'engage depuis plus de 75 ans au service de la souveraineté scientifique, technologique et industrielle de la France et de l'Europe pour un présent et un avenir mieux maîtrisés et plus sûrs. Implanté au cœur des territoires équipés de très grandes infrastructures de recherche, le CEA dispose d'un large éventail de partenaires académiques et industriels en France, en Europe et à l'international. Les 20 000 collaboratrices et collaborateurs du CEA partagent trois valeurs fondamentales : * La conscience des responsabilités * La coopération * La curiosité ### **Référence** 2026-42007 ### **Description de l'unité** The French Atomic Energy Commission (CEA) is a key player in research, development, and innovation. Drawing on the widely acknowledged expertise gained by its 16,000 staff spanned over 9 research centers with a budget of 4.1 billion Euros, CEA actively participates in more than 400 European collaborative projects with a large number of academic (notably as a member of Paris-Saclay University) and industrial partners. Within the CEA Technological Research Division, the CEA-List institute addresses the challenges coming from smart digital systems. Among other activities, CEA List's Software Safety and Security Laboratory (LSL) research teams design and implement automated analysis in order to make software systems more trustworthy, to exhaustively detect their vulnerabilities, to guarantee conformity to their specifications, and to accelerate their certification. The lab recently extended its activities on the topic of AI trustworthiness and gave birth to a new research group: AISER (Artificial Intelligence Safety, Explainability and Robustness).