Sign inGet started
Dataset · Hugging Face

pkuHaowei/kumo-hard

🌩️ KUMO: Generative Evaluation of Complex Reasoning in Large Language Models KUMO is a novel benchmark for systematically evaluating complex reasoning capabilities in Large Language Models (LLMs) through procedurally generated reasoning games. This repository contains the official implementation of our research paper. 📂 Benchmark Dataset The KUMO benchmark introduces procedurally generated reasoning games structured around: 🔍 Truth Set ($T$): Possible… See the full description on the dataset page: https://huggingface.co/datasets/pkuHaowei/kumo-hard.

Author / organizationpkuHaowei
Downloads262 (as reported by Hugging Face)
Likes4
Created10 April 2025
Last updated at source10 April 2025
Embed this entry
<iframe src="https://silytics.si/embed/item/08cfeec2-a6df-4e44-9a57-22804b1c83a8" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Popularity, last 3 days

262 now (+1 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.

Recent changes

  • 17 Oct 2026 Description: 🌩️ KUMO: Generative Evaluation of Complex Reasoning in Large Language Models KUMO is a novel benchmark for systematically evaluating complex reasoning capabilities in Large Language Models (LLMs) through procedurally generated reasoning ga → 🌩️ KUMO: Generative Evaluation of Complex Reasoning in Large Language Models KUMO is a novel benchmark for systematically evaluating complex reasoning capabilities in Large Language Models (LLMs) through procedurally generated reasoning ga

Changes detected by Silytics between refreshes of the source.

More from pkuHaowei

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.