Internship: Person-Centric Multimodal Large Language Model F/M

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Published on 28/10/2025

Contract type: Internship
Work time: Full time
Location Meylan

About NAVER LABS Europe

NAVER LABS Europe is part of the R&D division of NAVER, Korea’s leading Internet portal and a global tech company with a range of services that include search, commerce, content, fintech, robotics and cloud.

The position

Multimodal Large Language Models (MLLMs) [1,2] have recently made substantial progress in linking visual and linguistic understanding.

However, most current approaches treat visual content as a set of global features, overlooking fine-grained human-centered information that is essential for true multimodal reasoning. MLLMs typically offer limited opportunities for explanation or reasoning about the tasks they are given, due to an absence of explicit representation of multimodal objects. This lack of transparency is particularly problematic in human-centered applications, especially in robotics.

This internship aims to explore person-centric multimodal language modeling, building on recent progress in Video Question Answering (VQA) [7] and social interaction understanding.

The core idea is to extend Vision-Language Models (VLMs) with structured, per-person features that encode geometry, motion, and audio cues to enable a richer understanding of human activity and interaction.

This internship will investigate the integration of low-dimensional 3D pose embeddings, per-person audio streams, and inter-person relational cues into multimodal transformers.

The objective is to evaluate these architectures on VQA-style and captioning benchmarks that involve social and multimodal reasoning, such as Social-IQ [4-5], STAR [6], and NExt-QA [3].

This internship will contribute toward developing multimodal reasoning systems capable of understanding not just what happens in a scene, but who does it, how, and why.

Your mission:

Propose an approach for efficiently adapting person-oriented representations from visual and audio modalities to an MLLM
Create a benchmark based on existing datasets, focusing on challenging person-centric instances
Propose an evaluation methodology outlining the benefits of the added features in terms of explainability

Details:

Duration: six months
Start date: as soon as possible

About the research team

In the Interactive Systems group, we develop AI capabilities that enable robots to interact safely with humans, other robots, and systems. For a robot to be truly useful, it must represent its knowledge of the world, share what it learns, and interact with other agents, particularly humans. Our research integrates expertise in human-robot interaction, natural language processing, speech, information retrieval, data management, and low-code/no-code programming to create AI components that empower next-generation robots to perform complex real-world tasks.

What we're looking for

Master’s student with an excellent profile or already enrolled in a PhD program
Strong background in computer vision and deep learning
Good understanding of multimodal transformers, VLMs/LLMs, and 3D human representations
Experience with frameworks such as PyTorch, torchvision, and Hugging Face Transformers
Familiarity with LoRA fine-tuning, feature fusion, and multimodal training strategies
Curiosity for human-centered AI and an interest in modeling social interactions in videos

What we offer

We foster a collaborative environment dedicated to ambitious, multidisciplinary projects that translate advanced research into impactful, real-world solutions, supported by 30+ years of experience in AI and related fields.
Flexible work/life balance.
We are an equal opportunity employer that hires based on skills, experience, and merit. We foster an inclusive and diverse workplace where all qualified candidates are considered fairly, regardless of background.
We’re based in Meylan, close to Grenoble, a city that offers the perfect balance of urban life, cutting-edge research and technology, and spectacular mountain landscapes that provide countless opportunities to relax, recharge, and enjoy the outdoors.

All applications will be carefully considered, even if not all required skills are met. We value diverse backgrounds and the potential of each candidate, and we offer training to support the development of necessary skills.

NAVER LABS, co-located in Korea and France, is the organization dedicated to preparing NAVER’s future. Scientists at NAVER LABS Europe are empowered to pursue long-term research problems that, if successful, can have significant impact and transform NAVER. We take our ideas as far as research can to create the best technology of its kind. Active participation in the academic community and collaborations with world-class public research groups are, among others, important ways to achieve these goals. Teamwork, focus and persistence are important values for us.

When applying for this position online, please don't forget to upload your CV and cover letter. Incomplete applications will not be considered.

NAVER LABS Europe is subject to French jurisdiction requiring organisations to stipulate that a job/internship is open to both women and men. None of our jobs/internships are gender specific.

References

LLaVa: Large Language and Vision Assistant, Lui et al, NeurIPS'23
Qwen2.5-VL, Bai et al, arXiv
NExt-QA: Next Phase of Question-Answering for Explaining Temporal Actions, Xiao et al, CVPR'21
Social-IQ: A Question Answering Benchmark for Artificial Social Intelligence, Zadeh et al, CVPR'19
Social-IQ 2.0 Challenge, ICCV'23
STAR: A Benchmark for Situated Reasoning in Real-World Videos, Bo et al, NeurIPS'21
MoReVQA: Exploring Modular Reasoning Models for Video Question Answering, Min et al, CVPR'24

Réf: e86391dc-39c7-4536-9196-4b8aaaa3d5aa

This position has been filled.

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