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English(EN) Mi:dm K 2.5 Pro hits 80.9% on MMLU-Pro but only 10% on long-context reasoning — independently measured, not self-reported. https:// olud.ai/leaderboard.html # L

Mi:dm K 2.5 Pro 在 MMLU-Pro 上表现强劲,但在长上下文方面遇到困难

Mi:dm K 2.5 Pro 模型在 MMLU-Pro 基准测试中取得了 80.9% 的分数。然而,其在长上下文推理任务上的表现明显较低,仅为 10%。这些结果是独立测量的,而非模型创建者自报。 AI

影响 这一基准测试结果表明,尽管在一般知识任务上表现强劲,但当前模型在处理扩展上下文方面可能存在局限性。

排序理由 该集群报告了 AI 模型的基准测试表现,属于研究范畴。[lever_c_demoted from research: ic=1 ai=1.0]

在 Mastodon — fosstodon.org 阅读 →

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Mi:dm K 2.5 Pro 在 MMLU-Pro 上表现强劲,但在长上下文方面遇到困难

本文如何被排名

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
该集群报告了 AI 模型的基准测试表现,属于研究范畴。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
model release, other
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
63 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

报道来源 [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    Mi:dm K 2.5 Pro 在 MMLU-Pro 上达到 80.9%,但在长上下文推理上仅为 10% — 独立测量,非自报。https:// olud.ai/leaderboard.html # L

    Mi:dm K 2.5 Pro hits 80.9% on MMLU-Pro but only 10% on long-context reasoning — independently measured, not self-reported. https:// olud.ai/leaderboard.html # LLM # Benchmarks # OpenSource # AI