ComplexConstraints: A Benchmark for Multi-Constraint Instruction Following

A benchmark set of 75 items for evaluating language models on complex, multi-constraint instructions, created by SurgeAI. Each item is a realistic prompt paired with 10–40 evaluation criteria, totaling 1,559 criteria for rubric-based grading. The dataset was last updated on June 3, 2026.

Use Cases

• Benchmarking LLM performance on complex instructions based on the 75 realistic prompts.
• Developing automated evaluation metrics based on the 1,559 rubric-style criteria.
• Training or fine-tuning models for better constraint adherence based on the prompt-criteria pairs.

Strengths

• Contains 75 distinct benchmark items (CIF-001–CIF-075) for structured evaluation.
• Provides 1,559 total evaluation criteria, averaging 10–40 criteria per prompt for detailed assessment.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

surgeai on Hugging Face

Collection Method

Likely created as a structured benchmark for research purposes.

Freshness

Last updated 2026-06-03 19:49:55; freshness should be verified.