[2603.28813] The impact of multi-agent debate protocols on debate quality: a controlled case study

[2603.28813] The impact of multi-agent debate protocols on debate quality: a controlled case study

arXiv - AI 3 min read

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Abstract page for arXiv paper 2603.28813: The impact of multi-agent debate protocols on debate quality: a controlled case study

Computer Science > Multiagent Systems arXiv:2603.28813 (cs) [Submitted on 28 Mar 2026] Title:The impact of multi-agent debate protocols on debate quality: a controlled case study Authors:Ramtin Zargari Marandi View a PDF of the paper titled The impact of multi-agent debate protocols on debate quality: a controlled case study, by Ramtin Zargari Marandi View PDF HTML (experimental) Abstract:In multi-agent debate (MAD) systems, performance gains are often reported; however, because the debate protocol (e.g., number of agents, rounds, and aggregation rule) is typically held fixed while model-related factors vary, it is difficult to disentangle protocol effects from model effects. To isolate these effects, we compare three main protocols, Within-Round (WR; agents see only current-round contributions), Cross-Round (CR; full prior-round context), and novel Rank-Adaptive Cross-Round (RA-CR; dynamically reorders agents and silences one per round via an external judge model), against a No-Interaction baseline (NI; independent responses without peer visibility). In a controlled macroeconomic case study (20 diverse events, five random seeds, matched prompts/decoding), RA-CR achieves faster convergence than CR, WR shows higher peer-referencing, and NI maximizes Argument Diversity (unaffected across the main protocols). These results reveal a trade-off between interaction (peer-referencing rate) and convergence (consensus formation), confirming protocol design matters. When consensus is...

Originally published on April 01, 2026. Curated by AI News.

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