Serwan Jassim — accepted AI-conference papers

2025

iVISPAR — An Interactive Visual-Spatial Reasoning Benchmark for VLMs

Julius Mayer, Mohamad Ballout, Serwan Jassim, Farbod Nosrat Nezami, Elia Bruni

EMNLP 2025

Vision-Language Models (VLMs) are known to struggle with spatial reasoning and visual alignment. To help overcome these limitations, we introduce iVISPAR, an interactive multimodal benchmark designed to evaluate the spatial reasoning capabilities of VLMs acting as agents. iVISPAR is based on a varia

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2024

GRASP: A Novel Benchmark for Evaluating Language GRounding and Situated Physics Understanding in Multimodal Language Models

Serwan Jassim, Mario Holubar, Annika Richter, Cornelius Wolff, Xenia Ohmer, Elia Bruni

IJCAI 2024poster

This paper presents GRASP, a novel benchmark to evaluate the language grounding and physical understanding capabilities of video-based multimodal large language models (LLMs). This evaluation is accomplished via a two-tier approach leveraging Unity simulations. The first level tests for language gro…

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