A Dataset for Dynamic Human Preferences for Vision Language Models

• URL: http://arxiv.org/abs/2606.07653v1
• Date: Tue, 02 Jun 2026 23:08:29 GMT
• Title: A Dataset for Dynamic Human Preferences for Vision Language Models
• Abstract summary: This work introduces a new benchmark for evaluating the ability of Vision Language Models to understand dynamic human-preferences.<n>We provide an automated pipeline for generating this benchmark with variations on image dependence, a dynamic multi-modal human-preference dataset, and evaluations of state-of-the-art models on the novel benchmark.
• Score: 6.379494871147752
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Given the increased adoption of Vision Language Models (VLMs) in human-interactive settings, it is important that we evaluate how well these models can adapt to real-time preferences for different users. While an increasing number of vision-language benchmarks have recently been introduced, they focus largely on evaluating static capabilities and generally-held preferences learned from extensive training data. This work introduces a new benchmark for evaluating the ability of VLMs to understand dynamic human-preferences, i.e. preferences that are passed in-context at inference time. We provide an automated pipeline for generating this benchmark with variations on image dependence, a dynamic multi-modal human-preference dataset, and evaluations of state-of-the-art models on the novel benchmark.

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