MARS: Multi-Specialist LLM Relay System for Competitive Programming

• URL: http://arxiv.org/abs/2608.23918v1
• Date: Mon, 24 Aug 2026 23:51:02 GMT
• Title: MARS: Multi-Specialist LLM Relay System for Competitive Programming
• Abstract summary: MARS (Multi-Agent Relay of Specialized LLMs) is a prompt-only framework in which each agent is a topic specialist.<n>A starter writes an initial C++17 solution, and each subsequent turn runs the candidate against public examples in a sandbox.<n>A single infrastructure-fixer pass normalizes boilerplate at the end.
• Score: 3.8421682531018564
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Large Language Models excel at code generation, yet competitive programming exposes a persistent failure mode: existing multi-agent pipelines distribute work over generic planner, coder, and debugger roles and delegate the choice of algorithmic technique to the backbone alone. We present MARS (Multi-Agent Relay of Specialized LLMs), a prompt-only framework in which each agent is a topic specialist---dynamic programming, graphs, strings, geometry, and so on---grounded by retrieval-augmented generation over an algorithm-theory corpus. Given a problem, retrieval selects a small team of relevant specialists; a starter writes an initial C++17 solution, and each subsequent turn runs the candidate against public examples in a sandbox, lets the active specialist keep, repair, or hand off the draft, and forwards a structured packet to the next specialist. A single infrastructure-fixer pass normalizes boilerplate at the end. On the CodeContests test split with Gemma 4, MARS reaches $0.624 \pm 0.006$ pass rate at $2.3$ recorded pipeline stages per task ($+14.4$ percentage points over direct prompting), closing most of the gap to CodeSIM ($0.731$) at $3.3{\times}$ lower wall-clock cost and substantially smaller variance in per-task token spend. The source code is available on GitHub: https://github.com/fckand/mars.

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