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该论文提出 Packed-SS，一种自投机解码调度方案，通过让扩散起草器在验证当前草稿时提前一个调用构建下一草稿，实现单次模型调用完成验证与起草，输入规模随投机宽度线性增长，并在 Nemotron 3B/8B 与 SetDLM 1.7B 上取得更高吞吐量。
提出DCOCO（DFlash Contextual Corrector），一种轻量级机制，在保持并行草稿生成的同时恢复块内上下文依赖，在四个验证器骨干和十个基准上实现最高达6.6倍的推理加速，并在并发服务场景下显著优于现有方法。
TokenRouter 是一个面向 token 级 LLM 路由的高效推理服务系统，采用「请求中心编程、模型中心执行」架构与延迟批调度策略，实现较现有系统 2.01–64.15 倍的解码吞吐提升。
DScout 通过将扩散草稿器的训练与推理分解为前缀接受度和延迟权衡，提升了推测解码的吞吐量，在 Qwen3-4B 和 Qwen3-8B 上分别实现 3.84 倍和 4.14 倍的平均加速。
DynaResize is a runtime GPU reallocation system that dynamically switches GPUs between Rollout and Training stages during RL-based LLM post-training, improving throughput by 66.5% and reducing execution time by 33% over static configurations.
DeepSeek released DSpark, a speculative decoding method that boosts throughput by 51% to 400% for V4 Flash & Pro, along with the open-source DeepSpec codebase for training and evaluating draft models.
Ray Serve LLM achieves 4.4x and 24.8x throughput improvements on prefill- and decode-heavy workloads via direct streaming, a new vLLM V2 executor backend, and HAProxy ingress, now available in Ray 2.56 in partnership with Google Cloud and vLLM.
ServiceNow releases SuperApriel-15B-Instruct, a single 15B checkpoint offering 8 mixer presets that trade between 1× and 10.7× decode throughput while maintaining up to 96% quality on 32K contexts.