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This is a Plain English Papers summary of a research paper called . If you like these kinds of analysis, you should join or follow us on .
Overview
AI systems like large language models (LLMs) are now pretty good at solving complex problems through step-by-step reasoning. But they often use too many words or steps, wasting time and computing resources. It's like watching someone solve a simple math problem by writing three...
Overview
- L1 is a reinforcement learning system for controlling reasoning length in LLMs
- Balances reasoning quality with efficiency by optimizing token usage
- Outperforms existing methods on several reasoning benchmarks
- Uses sparse rewards to train models on when to stop reasoning
- Achieves significant improvements (up to 41%) in reasoning step efficiency
AI systems like large language models (LLMs) are now pretty good at solving complex problems through step-by-step reasoning. But they often use too many words or steps, wasting time and computing resources. It's like watching someone solve a simple math problem by writing three...