Vision Language Models Vlms Papers

This page lists 1 peer-reviewed paper in the research area of Vision Language Models Vlms in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.

Papers (1 of 1)

Visual cognition in multimodal large language models

Authors: LM Schulze Buschoff, E Akata, M Bethge

Year: 2025

Published in: Nature Machine ..., 2025 - nature.com

Institution: Max Planck Institute

Research Area: Visual Cognition, Multimodal Large Language Models (MLLMs), Vision-Language Models (VLMs)

Discipline: Cognitive Science, Artificial Intelligence, Computer Vision

Vision-based large language models show proficiency in visual data interpretation but fall short in human-like abilities for causal reasoning, intuitive physics, and social cognition.

Methods: Controlled experiments evaluating model performance on tasks related to intuitive physics, causal reasoning, and intuitive psychology using visual processing benchmarks.

Key Findings: Model capabilities in understanding physical interactions, causal relationships, and social preferences.

DOI: https://doi.org/10.1038/s42256-024-00963-y

Citations: 70