POLARIS trains Qwen3.5-9B via GRPO with LLM-as-judge rewards and human-reference injection, yielding a model competitive with larger open-weight models on length adherence and quality, including generalization to 3x training length.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Position paper claiming that AI safety requires explicit runtime controllability and introducing ControlBench to demonstrate gaps in existing alignment methods.
citing papers explorer
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POLARIS: Guiding Small Models to Write Long Stories
POLARIS trains Qwen3.5-9B via GRPO with LLM-as-judge rewards and human-reference injection, yielding a model competitive with larger open-weight models on length adherence and quality, including generalization to 3x training length.
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Position: AI Safety Requires Effective Controllability
Position paper claiming that AI safety requires explicit runtime controllability and introducing ControlBench to demonstrate gaps in existing alignment methods.