Datasets:
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- ICML 2025 Long-Context Foundation Models Workshop Accepted.
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A simple context interference evaluation.
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> **Update:Sept.6-mergerd into Moonshot/Kimi AI's internal eval tools and under review by a
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## TL;DR
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We identify a task that is **super easy for humans** but where all LLMs—from early 0.1B to the most modern 600B+ (GPT-5, Grok-4, Gemini, DeepSeek, etc.)—consistently **fail in the Same Way**. This pinpoints the **core challenge of MRCR**
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- ICML 2025 Long-Context Foundation Models Workshop Accepted.
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A simple context interference evaluation.
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- Update: This dataset is integrated into Moonshot AI(Kimi)'s **internal benchmarking framework** for assessing ** tracking capacity and context interference in LLM/agents**.
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> **Update:Sept.6-mergerd into Moonshot/Kimi AI's internal eval tools and under review by a xAI(Grok)'s' eval team**
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## TL;DR
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We identify a task that is **super easy for humans** but where all LLMs—from early 0.1B to the most modern 600B+ (GPT-5, Grok-4, Gemini, DeepSeek, etc.)—consistently **fail in the Same Way**. This pinpoints the **core challenge of MRCR**
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