FIELD NOTES TOPIC

multimodal ai

3 notes, newest first.

  1. Breaking the weakest link to evade vision language models

    Source note ·

    The authors investigate the vulnerability of Vision Language Models (VLMs) to adversarial attacks, which can disrupt or force the models' interpretation of visual inputs. They propose a gradient-based attack method…

  2. What Current AI Benchmarks Leave Unmeasured: Modality, Search, Citations, and Implications (for Safety Evaluations)

    Source note ·

    The study audits the assumptions made in large language model (LLM) benchmark evaluations, focusing on one popular LLM - ChatGPT. The research compares two access modalities (chat UI and API), with and without web…

  3. Harnessing Textual Refusal Directions for Multimodal Safety

    Source note ·

    Researchers propose a new approach called Modality-Agnostic Refusal Steering (MARS) to improve safety in Multimodal Large Language Models without requiring unsafe multimodal data. MARS uses textual refusal directions…