MLLMs Tool-Calling Flaws: What Builders Should Change
This story is from 2026-10-22. It is preserved in the archive; the latest stories are on the live feed.
MLLMs' Blind Spot Researchers have found that agentic multimodal large language models (MLLMs) often fail to refuse when calling tools like zooming or tagging. This behavior can lead to inaccurate outcomes and undermine the reliability of AI-driven processes. The study highlights a critical oversig…
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- 2026-10-22 03:00 · DEV Community — AI
MLLMs Tool-Calling Flaws: What Builders Should Change