AIR: Adaptive Interleaved Reasoning with Code in MLLMs
Following the paradigm shift initiated by OpenAI o3, interleaved reasoning with code to enhance multimodal large language models (MLLMs) has become a...
Summary
Following the paradigm shift initiated by OpenAI o3, interleaved reasoning with code to enhance multimodal large language models (MLLMs) has become a pivotal research frontier. The existing literature focuses primarily on tool-use within vision-perception tasks. However, such approaches typically rely on predefined heuristics for visual manipulation and are inherently incapable of addressing numer
Why it matters
This is part of the steady stream of AI work that reshapes how researchers and builders think about what’s possible. The full details are in the original source below — worth reading directly rather than relying on a brief summary.
Read the original
The primary source has the full paper, announcement, or reporting:
→ https://arxiv.org/abs/2606.23678v1
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