SteerDistill Quantizes LLM Agents
The story so far
qwen introduced SteerDistill, a method for quantizing LLM agents using closed-loop teacher guidance. This method scored 1.67-2.18 points higher on average than the strongest quantization baseline under W4A16, achieved a success rate of 1.84 percentage points higher on τ^2-Bench, and reduced training GPU hours by 67%.
AI-written from the reports · Updated 2 days ago
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- Hugging Face Daily PapersSteerDistill: Closed-loop teacher guidance for quantifying LLM agents
SteerDistill quantizes LLM agents through closed-loop teacher guidance, achieving an average score 1.67-2.18 points higher than the strongest quantization baseline on W4A16, a success rate of 1.84 percentage points on τ^2-Bench, and reducing training GPU hours by 67%.
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