Two Heads are Better Than One: Test-time Scaling of Multi-agent Collaborative Reasoning M1-32B is a 32B-parameter large language model fine-tuned from Qwen2.5-32B-Instruct on the M500 dataset—an interdisciplinary multi-agent collaborative reasoning dataset. M1-32B is optimized for improved reasoning, discussion, and decision-making in multi-agent systems (MAS), including frameworks such as AgentVerse. Code: https://github.com/jincan333/MAS-TTS Project page: https://github.com/jincan333/MAS-TTS — 🧠 Enhanced Collaborative Reasoning Trained on real multi-agent traces involving diverse roles like Expert Recruiter, Problem Solvers, and Evaluator. — 🗣️ Role-Aware Dialogue Generation Learns to reason and respond from different expert perspectives based on structured prompts. — ⚙️ Optimized for Multi-Agent Systems Performs well as a MAS agent with adaptive collaboration and token budgeting. Table Caption: Performance comparison on general understanding, mathematical reasoning, and coding tasks using strong reasoning and non-reasoning models within the AgentVerse framework. Our method achieves substantial improvements over Qwen2.5 and s1.1-32B on all tasks, and attains performance…
Модальности:
Генерация текста
Области применения:
Генерация кода Математика Логика и рассуждение Диалог / чат
Задача: Генерация текста
Автор: Can111
Теги: qwen2, multi-agent systems, multiagent-collaboration, reasoning, mathematics, code, conversational, zho
Лайков: 3 | Загрузок: 36
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
