Papers with VLM agent pipeline
Value-Spectrum: Quantifying Preferences of Vision-Language Models via Value Decomposition in Social Media Contexts (2025.acl-long)
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| Challenge: | Recent advances in Vision-Language Models (VLMs) have broadened the scope of multimodal applications, but evaluations often neglect abstract dimensions such as personality traits and human values. |
| Approach: | They propose a Visual Question Answering (VQA) benchmark based on Schwartz’s value dimensions that capture core human values guiding people’s preferences and actions. |
| Outcome: | The proposed model can be used to evaluate visual question answering (VQA) tasks and to simulate diverse personas. |