This paper presents a pilot study aimed at introducing multi-agent debate
into multimodal reasoning. The study addresses two key challenges: the
trivialization of opinions resulting from excessive summarization and the
diversion of focus caused by distractor concepts introduced from images. These
challenges stem from the inductive (bottom-up) nature of existing debating
schemes. To address the issue, we propose a deductive (top-down) debating
approach called Blueprint Debate on Graphs (BDoG). In BDoG, debates are
confined to a blueprint graph to prevent opinion trivialization through
world-level summarization. Moreover, by storing evidence in branches within the
graph, BDoG mitigates distractions caused by frequent but irrelevant concepts.
Extensive experiments validate BDoG, achieving state-of-the-art results in
Science QA and MMBench with significant improvements over previous methods.

本文提出了一种名为 “图像蓝图辩论” 的顶 - 下述式多模式推理方法，解决了多分类结果过于概括和由图像引入的分散注意力的挑战，并在科学问答和 MMBench 中实现了最先进的结果。