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General365
General365 is a manually curated benchmark for evaluating general reasoning in LLMs across difficult and diverse tasks, with a focus on reasoning over K-12-scope knowledge rather than domain-specialist knowledge.
The official repository presents General365 as the benchmark release for the paper on general reasoning under high difficulty and diversity, with public questions, variants, model-response formatting, grading code, project links, leaderboard materials, and a Hugging Face dataset link. Use this as a first read, not a recommendation. Open the original project before trusting details like terms, limits, privacy, cost, setup, or safety.
What it is
A general-reasoning benchmark
General365 is framed as a benchmark for testing broad reasoning ability, with manually crafted seed problems and variants intended to reduce overreliance on narrow domain knowledge or rote memorization.
Why it stands out
Difficulty and diversity focus
General365 combines high-difficulty tasks and broad scenario coverage with K-12-scope knowledge constraints, held-out questions, and hybrid scoring that mixes rule-based and model-based checks.
Availability
Repo, dataset, project page, and leaderboard
The official materials include the GitHub repository, paper link, project page, leaderboard, Hugging Face dataset, grading script, model-response format, and example workflow for running evaluations.
Why it matters
What makes it useful
General365 tries to evaluate general reasoning without leaning only on specialist academic knowledge. Its manually curated problems, variants, held-out note, grading script, leaderboard materials, and dataset link give readers a benchmark design to inspect.
What to know
Where it fits
Use it to compare reasoning across difficult, varied problems that stay within broadly accessible K-12 knowledge. Its held-out questions and hybrid scoring help structure that comparison, but one benchmark cannot decide a model's overall intelligence or fit for a real task.
Notable points
What stands out
The benchmark uses 365 manually curated seed problems expanded into 1,095 variants, with a held-out test set and hybrid scoring workflow. Its leaderboard materials show how that design is used to compare model performance.
Before using
What to review
Which public questions, variants, and held-out limitations are described in the official materials.
The grading script, model-response JSONL format, and scoring method before adapting the benchmark.
Whether the benchmark is being used to compare general reasoning, data contamination risk, or a narrower model capability claim.
Reader fit
Who may find it relevant
Readers following LLM reasoning benchmarks and model-comparison methods.
Builders and researchers comparing difficult general-reasoning tasks across model families.
Less relevant for readers looking for a model checkpoint, finished app, or agent framework.
Editorial note
Why LifeHubber lists it
General365 asks a useful narrower question: can a model reason across difficult and varied tasks without depending on specialist knowledge? Its variants and held-out design support that comparison, while contamination, grading choices, and real-world performance still need separate judgment.
Source links
Source materials
Reader note
Before relying on this entry
LifeHubber lists entries to help readers inspect AI projects, not to endorse them or prove they are safe, suitable, accurate, maintained, or right for a specific use. We do not verify every entry in depth. Before relying on anything listed, review the original materials, terms, privacy practices, limits, and risks that matter for your situation.
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