Do More Agents Help? Controlled and Protocol-Aligned Evaluation of LLM Agent Workflows
Does adding more agents help an LLM workflow once compared systems share the same benchmark loader, tool access, answer contract, usage accounting, and trajectory logging? We introduce BenchAgent, an evaluation framework that places single-agent, fixed multi-agent (MAS), and evolving MAS workflows under one normalized execution and logging protocol. BenchAgent evaluates these substrate-internal workflows across ten reasoning, coding, and tool-use benchmarks with GPT-4.1, and separately reports a
Record details
Published: 4 June 2026
Source: arXiv
Category: Research
Topics: Agents & autonomy
Retrieved: 14 July 2026
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ethics.ai (4 June 2026), “Do More Agents Help? Controlled and Protocol-Aligned Evaluation of LLM Agent Workflows,” evidence record 1461, https://ethics.ai/record/1461 (originally published by arXiv).
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