Niels Rogge

中文参考

介绍带有Code的论文LCP服务器！ 为了庆祝它的发布，我请Claude Code通过@typesafeai使用“search_papers”工具研究Jev的架构。 这是它的结果： “如果Jev在架构上是任何公共的东西，那么它就是一个大型模式条件双向编码器，具有并行标签查询头（GLiNER/ML-Decoder形状），用适当的评分规则RL目标（RLCC形状）进行训练，扩展范围远远超过了这些论文操作的~ 150 M参数范围--“既不小，也不LLM”符合这一点。40-200倍的加速与消除自回归是一致的，而不是任何奇异机制。"

原帖全文 / EN

Introducing the Papers with Code MCP server! To celebrate its release, I've asked Claude Code to research the architecture of Jev by @typesafeai using the `search_papers` tool. Here's what it came up with: "If Jev is architecturally anything public, it's a large schema-conditioned bidirectional encoder with parallel label-query heads (GLiNER/ML-Decoder shape) trained with a proper-scoring-rule RL objective (RLCR shape), scaled far past the ~150M-param range those papers operate in — "neither small nor an LLM" fits that. The 40–200× speedup is consistent with removing autoregression, not with any exotic mechanism."