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Research questionHow can language models reliably follow instructions containing many simultaneous constraints?As prompts accumulate explicit requirements, language models often satisfy some while overlooking others. Existing datasets and benchmarks generally stop at ten constraints, making performance on denser real-world instructions difficult to train for and measure.
AI
Evaluation & Benchmarks
LLM Pretraining & Post-training
Natural Language Processing
Reasoning
Reinforcement Learning
Latest papersRecent research connected to this question, newest first.RECAST: Expanding the Boundaries of LLMs' Complex Instruction Following with Multi-Constraint DataThe source describes RECAST, which extracts constraints from real-world prompt-response pairs and synthesizes RECAST-30K with 30,000 instances across 19 constraint types. It reports finetuning results, rule-based validators for quantitative constraints, LLM-based validators for qualitative constraints, and reinforcement-learning reward design based on constraint verifiability.research paper · Sep 3, 2026
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