Slm-mux Orchestrating small language models for reasoning скачать в хорошем качестве

Slm-mux Orchestrating small language models for reasoning

Paper: https://arxiv.org/abs/2510.05077 Title: Slm-mux: Orchestrating small language models for reasoning Authors: Chenyu Wang, Zishen Wan, Hao Kang, Emma Chen, Zhiqiang Xie, Tushar Krishna, Vijay Janapa Reddi, Yilun Du Abstract: With the rapid development of language models, the number of small language models (SLMs) has grown significantly. Although they do not achieve state-of-the-art accuracy, they are more efficient and often excel at specific tasks. This raises a natural question: can multiple SLMs be orchestrated into a system where each contributes effectively, achieving higher accuracy than any individual model? Existing orchestration methods have primarily targeted frontier models (e.g., GPT-4) and perform suboptimally when applied to SLMs. To address this gap, we propose a three-stage approach for orchestrating SLMs. First, we introduce SLM-MUX, a multi-model architecture that effectively coordinates multiple SLMs. Building on this, we develop two optimization strategies: (i) a model selection search that identifies the most complementary SLMs from a given pool, and (ii) test-time scaling tailored to SLM-MUX. Our approach delivers strong results: Compared to existing orchestration methods, our approach achieves up to 13.4% improvement on MATH, 8.8% on GPQA, and 7.0% on GSM8K. With just two SLMS, SLM-MUX outperforms Qwen 2.5 72B on GPQA and GSM8K, and matches its performance on MATH. We further provide theoretical analyses to substantiate the advantages of our method. In summary, we demonstrate that SLMs can be effectively orchestrated into more accurate and efficient systems through the proposed approach. Tags: Machine Learning, Mathematics, Research, reinforcement learning, gan, ensemble, search, slm, mux, orchestrating, small, language, research paper, academic, study, analysis, tutorial, explained, breakdown, paper review, research summary, AI research, scientific paper, methodology, results, findings, innovation, technology, computing, algorithm, model, dataset, evaluation, performance, accuracy, efficiency, optimization, deep learning, neural networks, artificial intelligence Welcome to the Mayuresh Shilotri's Youtube . Maintained by Mayuresh Shilotri You can follow me at Blog - https://shilotri.com/ LinkedIn -   / mayureshshilotri   Twitter -   / mshilotri   Note: I only claim to have read the research paper and created a Video using AI tool. I am not the author. All intellectual heavy lifting was performed by the respective authors. 🙏