1
Prefill vs. Decode in LLM Inference
洞悉LLM推理中预填充与解码的差异，精准优化首字延迟与流式吞吐。
Article URL: https://www.parasail.io/blog/prefill-vs-decode-llm-inference Comments URL: https://news.ycombinator.com/item?id=49299992 Points: 2 # Comm…
2
LLM Router: Rethinking Routing with Prefill Activations
用prefill激活值重思LLM路由选择，为多模型推理调度开辟高效新路径。
arXiv:2603.20895v3 Announce Type: replace-cross Abstract: Existing routers rely on semantic query features or handcrafted features, which often fail t…
3
Sockpuppetting: Jailbreaking LLMs by Combining Prefilling with Optimization
新论文提出结合Preflilling与优化方法，低成本高效突破AI安全防线，揭秘LLM越狱攻击新思路。
arXiv:2601.13359v3 Announce Type: replace-cross Abstract: Prefill attacks are an effective and low-cost jailbreaking method, as they directly insert a…
4
LLM Serving Optimization with Variable Prefill and Decode Lengths
固定KV缓存内存下，智能调度不同长度请求，突破LLM推理效率瓶颈。
arXiv:2508.06133v4 Announce Type: replace-cross Abstract: We study offline scheduling for large language model (LLM) serving under a fixed KV-cache me…
5
Prefill/Decode-Aware Evaluation of LLM Inference on Emerging AI Accelerators
从Prefill/Decode阶段差异出发，为新兴AI加速器量身定制LLM推理性能评估方法，助力硬件选型与优化。
arXiv:2606.17104v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed in latency- and cost-sensitive settings, i…
6
Making Local LLM Fast
本地LLM提速秘笈：从Prefill到Decode，两分钟看懂推理加速核心环节
Article URL: https://bogdan.nimblex.net/programming/2026/06/10/making-local-llm-fast.html Comments URL: https://news.ycombinator.com/item?id=48489344 …