Natural Language Based Secure Federated Query Building

Le descriptif de l’offre ci-dessous est en Anglais_

**Type de contrat**: CDD

**Niveau de diplôme exigé**: Thèse ou équivalent

**Fonction**: Ingénieur scientifique contractuel

**A propos du centre ou de la direction fonctionnelle**:
Inria is the French National Institute for Research in Digital Science, of which the Inria Côte d'Azur University Center is a part. With strong expertise in computer science and applied mathematics, the research projects of the Inria Côte d'Azur University Center cover all aspects of digital science and technology and generate innovation. Based mainly in Sophia Antipolis, but also in Nice and Montpellier, it brings together 47 research teams and nine support services. It is active in the fields of artificial intelligence, data science, IT system security, robotics, network engineering, natural risk prevention, ecological transition, digital biology, computational neuroscience, health data, and more. The Inria Center at Université Côte d'Azur is a major player in terms of scientific excellence, thanks to the results it has achieved and its collaborations at both European and international level.

**Contexte et atouts du poste**:
INRIA is the French national research institute dedicated to computer science and applied mathematics and is a founding member of the World-Wide Web Consortium (W3C).

The Inria centre at Université Côte d'Azur includes 42 research teams and 9 support services. The centre's staff (about 500 people) is made up of scientists of different nationalities, engineers, technicians, and administrative staff. The teams are mainly located on the university campuses of Sophia Antipolis and Nice as well as Montpellier, in close collaboration with research and higher education laboratories and establishments (Université Côte d'Azur, CNRS, INRAE, INSERM...), but also with the regional economic players.

The Wimmics team works on the topic of AI on the Web, in particular knowledge graphs and (linked) data representation and processing in the Semantic Web. Wimmics contributes to knowledge formalization and semantic-based methods to extract, control, query, validate, infer, explain and interact with knowledge in epistemic communities on the Web. Wimmics has been involved in numerous European research projects (e.g., CoMMA, SevenPro, Sealife, Palette, Aloof, MIREL, HyperAgents) and national projects with a focus on knowledge representation and reasoning (KRR) in the Semantic Web (e.g., ISICIL, DataLift, SMILK, WASABI, D2KAB, Dekalog).

**Mission confiée**:
The goal is to design a conversational agent supporting a dialogical interaction to incrementally build queries distributed over several sources and explain the obtained results. The process will involve a question-answer session with the user and rely on the latest NLP techniques, in particular techniques coupling language models and knowledge graphs to augment the query context and ground the results in the graph [Wim1, Wim2, Wim5, Wim6].

Integrating results on how graph sampling can be used efficiently for federated query building (from other partners of the project) and our experience in building knowledge graph indexes [Wim3, Wim4], we plan to couple graph sampling techniques and Graph Retrieval Augmented Generation (GraphRAG) to augment language model prompts with context information. We will investigate how such a query-building process can align with the access control model proposed (Task 1) while ensuring that sampling strategies allow us to build efficient contexts (Task 2).

The targeted user interface should interactively and incrementally transform a natural language question into a federated SPARQL query while providing essential data provenance to build trust in the generated queries and their results. This interface will also follow an interaction design methodology for its specification and an HCI protocol for its user evaluation, for which we also have experience [Wim7].

**Principales activités**:
The work plan for that position includes:

- Language Model-based Query Building: design and prototyping of a conversational agent for dialogical building and refinement of a query, focusing on a first general scenario with open access.
- Interactive Source Selection with Access Control: access-control based RAG and natural language interactions to specify and select the sources and move towards a federated query integrating the security constraints.
- Present, explain, and justify results: visual and interactive interface and evaluation protocols to build trust in the obtained results and the conclusion of the dialog.
- Follow and manage the tasks of our team in the SaFE-KG project and participate in its calls and meetings and the supervision of internships.

Building on previous experience [wim1, wim5] we will start by adapting and evaluating the performances of different language models, large and small, on the different sub-tasks involved in having a dialogical access to the knowledge graphs. For this