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2026-08-21
日期、来源、摘要、可信度和合规说明均来自通过完整审核门禁与哈希校验的每日公开快照；周报发布后由同期完整发布包接管。
RSS 公开元数据：Measuring benchmark optimization in speech recognition。Update on GitHub Public voice AI benchmarks increasingly suggest that models are performing at human levels. Yet those scores don't always reflect how models work in the real-world. Since public benchmarks are open and widely used, models can also become optimized for the tests themselves. Their scores may improve because they have learned benchmark-specific patterns and not because they have become better at the underlying task. One reason is that traditional benchmarks overlook many of the conditions and qualities that make voice systems reliable, natural, contextually appropriate, and effective in practice. That's why we re... 来源：RSSHub。RSSHub public RSS metadata only; no full article body stored. Trafilatura public URL extraction; stored short extract only, no full article body, cookies, or headers.
打开公开来源RSS 公开元数据：Up to 3.2x Faster Inference with LFM2.5-DSpark。Today, we release DSpark draft model checkpoints for three models from our LFM2.5 family: LFM2.5-1.2B-Instruct, LFM2.5-2.6B, and LFM2.5-8B-A1B. These add a speculative decoding path that trades a minimal memory increase for a large decoding speedup without changing output quality: Faster inference: up to 3.18 throughput improvement on a GPU and up to 2.87x on-device. Toward on-device agentic inference: cuts function-calling latency by 57% on average for LFM2.5-2.6B Day-one support for llama.cpp and SGLang: LFM-compatible DSpark integration is open-sourced upstream How does DSpark work The decode phase in LLM inference is traditionally... 来源：RSSHub。RSSHub public RSS metadata only; no full article body stored. Trafilatura public URL extraction; stored short extract only, no full article body, cookies, or headers.
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