RLPE: Teaching LLMs to Prompt with Reinforcement Learning

arXiv cs.AIen

arXiv cs.AI

AI Global Wire

arXiv:2610.19062v1 Announce Type: new Abstract: Prompting is a widely used method for adapting general-purpose LLMs to domain-specific tasks. Effective prompts can be tedious to create manually, so prompt writing is increasingly handed to LLMs, with recent work training LLMs to write prompts for other models. These techniques either write prompts without observing how the task model behaves, blind to the failure modes the prompt should address, or must run alongside the task LLM at inference time, adding overhead to every query. Neither reflects how prompt engineering is often practiced. To close this gap, we introduce Reinforcement Learned Prompt Engineering (RLPE), which trains a model to

This is a short summary published by AI Global Wire. The full article is owned and hosted by arXiv cs.AI — open it there to read it in full.

Read the full story at arXiv cs.AI
  • Forskning

Related AI news