Tag: Multi-Agent
All the articles with the tag "Multi-Agent".
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Communicating Activations Between Language Model Agents
This paper introduces Activation Communication (AC), a novel method for inter-LLM communication using intermediate activations instead of natural language, achieving up to 27% performance improvement over traditional methods with significantly reduced compute across coordination games and reasoning benchmarks.
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AI agents may be worth the hype but not the resources (yet): An initial exploration of machine translation quality and costs in three language pairs in the legal and news domains
本文通过实证评估五种机器翻译范式,发现推理增强的大型语言模型(如o1-preview)在人工评估中表现出色,超越传统NMT,而多智能体系统虽具潜力,但因高计算成本和语言对表现不一致而受限。
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Do We Truly Need So Many Samples? Multi-LLM Repeated Sampling Efficiently Scales Test-Time Compute
This paper introduces ModelSwitch, a multi-LLM repeated sampling strategy that leverages answer consistency to dynamically switch models, achieving superior performance and 34% sample efficiency over single-LLM self-consistency across diverse datasets.
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LLM-Coordination: Evaluating and Analyzing Multi-agent Coordination Abilities in Large Language Models
本文通过LLM-Coordination基准测试框架,评估大型语言模型在纯协调游戏中的多智能体协调能力,发现其在环境依赖任务中表现优异但在心智理论推理和联合规划中存在显著不足,同时展现出对未见伙伴的零样本适应性。
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Less is More: Enhancing Structured Multi-Agent Reasoning via Quality-Guided Distillation
本文提出了一种质量导向的多代理框架,通过提示诱导、检索增强合成和奖励过滤从少量标注数据中提炼高质量监督信号,提升LLMs在低资源结构化推理任务中的性能。