Humanity's Last Exam (HLE) Benchmark

A Humanity's Last Exam (HLE) Benchmark is a phd-level science-focused ai evaluation benchmark that evaluates hle ai model performance on hle phd-level science questions (in domains like hle chemistry and hle biology) by OpenAI and Anthropic.

• AKA: HLE Benchmark, HLE, Humanity's Last Exam.
• Context:
  • It can typically assess Advanced AI Model Capability through hle phd-level question answering tasks.
  • It can typically challenge Frontier AI Model with hle text-only science problems.
  • It can typically reveal HLE Benchmark Error via hle answer validation processes.
  • It can typically demonstrate HLE Saturation Issue when hle frontier models achieve hle high performance.
  • It can typically include HLE Gotcha Question designed to exploit hle model weaknesses.
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  • It can often contradict HLE Peer-Reviewed Literature in approximately 30% of hle chemistry answers and hle biology answers.
  • It can often require HLE Literature Validation using hle research agents like hle paperqa2 system.
  • It can often feature HLE Adversarial Design prioritizing hle model failure over hle scientific accuracy.
  • It can often saturate with HLE Tool-Augmented Performance reaching 44% on hle grok4 model.
  • ...
  • It can range from being a Simple HLE Benchmark to being a Complex HLE Benchmark, depending on its hle question difficulty.
  • It can range from being a Text-Only HLE Benchmark to being a Tool-Augmented HLE Benchmark, depending on its hle model access mode.
  • It can range from being a Narrow-Domain HLE Benchmark to being a Multi-Domain HLE Benchmark, depending on its hle subject coverage.
  • It can range from being a Low-Accuracy HLE Benchmark to being a High-Accuracy HLE Benchmark, depending on its hle answer validation rigor.
  • It can range from being an Experimental HLE Benchmark to being a Production HLE Benchmark, depending on its hle deployment maturity.
  • ...
  • It can integrate with HLE Evaluation Framework for hle model testing.
  • It can connect to HLE Literature Research Agent for hle answer verification.
  • It can interface with HLE Error Auditing System for hle accuracy assessment.
  • It can communicate with HLE Performance Tracking System for hle score monitoring.
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• Example(s):
  • HLE Chemistry Subsets, such as:
    • HLE Oganesson Question demonstrating hle literature conflict.
    • HLE Chemical Property Question requiring hle deep chemistry knowledge.
    • HLE Reaction Mechanism Question testing hle chemical reasoning.
  • HLE Biology Subsets, such as:
    • HLE Raphidiopteran Question showing hle taxonomic challenge.
    • HLE Molecular Biology Question assessing hle biological system understanding.
    • HLE Evolutionary Biology Question evaluating hle theoretical knowledge.
  • HLE Physics Subsets, such as:
    • HLE Quantum Mechanics Question testing hle advanced physics concepts.
    • HLE Thermodynamics Question requiring hle mathematical derivation.
  • ...
• Counter-Example(s):
  • MMLU Benchmark, which covers broader topics but lacks hle phd-level depth.
  • SWE-Bench, which focuses on coding tasks rather than hle science questions.
  • GLUE Benchmark, which evaluates language understanding without hle domain expertise.
  • ImageNet Challenge, which tests visual recognition rather than hle scientific reasoning.
• See: PhD-Level AI Benchmark, AI Evaluation Benchmark, Science AI Benchmark, Benchmark Error Detection, Literature-Based Validation, Adversarial Benchmark Design, Frontier Model Evaluation, MMLU Benchmark, OpenAI, Anthropic.

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