A Picture Is Worth a Graph: A Blueprint Debate Paradigm for Multimodal Reasoning

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 that BDoG is able to achieve state-of-the-art results in ScienceQA and MMBench with significant improvements over previous methods. The source code can be accessed at https://github.com/thecharm/BDoG.

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Publication Details

Published
2024-10-26
DOI
https://doi.org/10.1145/3664647.3681102
Citations
2
Primary Topic
Multimodal Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.50
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article

A Picture Is Worth a Graph: A Blueprint Debate Paradigm for Multimodal Reasoning

Xiao-Yong Wei, Changmeng Zheng, Tat‐Seng Chua, Qing Li et al.
2 citations
Multimodal Machine Learning Applications
0.50
article

A Picture Is Worth a Graph: A Blueprint Debate Paradigm for Multimodal Reasoning

Xiao-Yong Wei, Changmeng Zheng, Tat‐Seng Chua, Qing Li, Dayong Liang, Wengyu Zhang
article en
2 citations

Abstract

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 that BDoG is able to achieve state-of-the-art results in ScienceQA and MMBench with significant improvements over previous methods. The source code can be accessed at https://github.com/thecharm/BDoG.

Hong Kong Polytechnic University (HK), National University of Singapore (SG), South China University of Technology (CN)
Decent work and economic growth
Openalex Percentile: Top 34%
Multimodal Machine Learning Applications
0.50
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