IF Multi Constraints Upto5: Training Data for Instruction-Following Models

IF-RLVR training data contains instructions with up to 5 constraints per instruction. The constraints are sampled from IFEval (25) and IFBench-Train (29). The dataset was created by AllenAI and last updated on October 2, 2025.

Use Cases

• Training models to follow complex multi-constraint instructions based on the described constraint sets.
• Benchmarking instruction-following accuracy based on the IFEval and IFBench-Train constraint sources.
• Analyzing model failure modes on synthetic instructions with up to 5 constraints.
• Generating synthetic training data for reinforcement learning from human feedback (RLHF) or related techniques.

Strengths

• Includes constraints from two established sources: IFEval (25 constraints) and IFBench-Train (29 constraints).
• Specifies a clear structure with up to 5 constraints per instruction.
• Created by a reputable AI research organization, AllenAI.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data is synthetic, which may not reflect real-world instruction distribution.

Provenance

Source

AllenAI

Collection Method

Synthetic generation, with constraints sampled from IFEval and IFBench-Train.

Time Range

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Freshness

Last updated 2025-10-02 17:49:46.

Geography

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