针对不同文章类型自动切换最优LLM模型，并集成80+正则清洗反AI痕迹，提升内容真实感。
I've been quietly running a small network of niche content sites for a few weeks. Two are live on real domains: afixu.com - home improvement and DIY t…
将LLM提示智能路由到最便宜且能胜任的模型，大幅降低AI API调用成本。
Article URL: https://github.com/Reactance0083/pydantic-ai-multi-llm-cost-optimizer Comments URL: https://news.ycombinator.com/item?id=48644688 Points:…
RouteJudge平台让LLM路由可复现且感知用户偏好，有助于精准高效地选择模型，已被ICML 2026研讨接收。
arXiv:2606.18774v1 Announce Type: new Abstract: We present RouteJudge, an online pairwise preference evaluation framework for LLM routing systems, wit…
工厂自动选模型，降本提效高达25%，让LLM路由像呼吸一样简单
Article URL: https://factory.ai/product/router Comments URL: https://news.ycombinator.com/item?id=48575781 Points: 1 # Comments: 0
LLM路由技术遭遇精度瓶颈？21种方法深度研究揭示突破之道。
arXiv:2606.07587v1 Announce Type: new Abstract: LLM routing has become a popular approach to improve the cost-quality trade-off of LLM services by dyn…
重新思考LLM路由的监督范式，从采样结果转向能力分布，为模型选择提供新视角。
arXiv:2606.06924v1 Announce Type: new Abstract: Existing LLM routing methods typically treat a model's single response to a query as its capability la…
用元学习隐式平衡成本与性能，自动选择最佳LLM，降本增效新范式。
arXiv:2606.06178v1 Announce Type: cross Abstract: Large language models (LLMs) present a trade-off between performance and cost, where more powerful m…
混合离线-在线学习的LLM路由器，用LinUCB上下文强盗算法智能选择模型，兼顾性能与成本
arXiv:2605.30736v1 Announce Type: cross Abstract: The rapid development of large language models, each with distinct capabilities and inference costs,…
AI模型路由新突破：用图画像解决冷启动难题，精准匹配LLM性能。
arXiv:2605.00180v2 Announce Type: replace-cross Abstract: LLM routing is increasingly important for selecting suitable models under diverse user needs…
用离线强化学习实现全局预算感知的LLM顺序路由，解决多模型调用成本与性能平衡难题。
arXiv:2605.25424v1 Announce Type: cross Abstract: Existing LLM routing frameworks treat queries as independent events, neglecting the sequential natur…
生产日志问答新方案：LogRouter实现自适应双层LLM路由，降低资源消耗。
arXiv:2605.18015v1 Announce Type: new Abstract: Production log analytics in self-hosted, resource-constrained environments requires natural-language a…
简单kNN方法竟击败复杂学习路由器，重新思考LLM路由预测建模的惊人发现！
arXiv:2505.12601v2 Announce Type: replace Abstract: As large language models (LLMs) grow in scale and specialization, routing--selecting the best mode…