[Submitted on 1 Feb 2026 (v1), last revised 25 Oct 2026 (this version, v3)]
Abstract:Complex question answering across text, tables and images requires integrating diverse information sources. A framework supporting specialized processing with coordination and interpretability is needed. We introduce DeALOG, a decentralized multi-agent framework for multimodal question answering. It uses specialized agents: Table, Context, Visual, Summarizing and Verification, that communicate through a shared natural-language log as persistent memory. This log-based approach enables collaborative error detection and verification without central control, improving robustness. Evaluations on FinQA, TAT-QA, CRT-QA, WikiTableQuestions, FeTaQA, and MultiModalQA show competitive performance. Analysis confirms the importance of the shared log, agent specialization, and verification for accuracy. DeALOG, provides a scalable approach through modular components using natural-language communication.
Submission history
From: Abhijit Chakraborty [view email]
[v1] Sun, 1 Feb 2026 03:26:52 UTC (2,885 KB)
[v2] Sun, 21 Jun 2026 07:42:56 UTC (9,947 KB)
[v3] Sun, 25 Oct 2026 06:43:47 UTC (589 KB)
