#discrete-optimization News & Analysis

2 articles tagged with #discrete-optimization. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBullisharXiv – CS AI · May 287/10

🧠

Prompt Codebooks: Discrete Compositional Optimization for Language Model Instruction Refinement

Researchers introduce Prompt Codebooks (PCO), a new framework for automatic prompt optimization that breaks down instructions into reusable, atomic components rather than treating prompts as fixed strings. The method achieves up to 30% performance gains over baseline approaches while reducing prompt lengths by 14x, enabling more efficient and adaptive language model instruction refinement.

AINeutralarXiv – CS AI · Jun 26/10

🧠

You Can Learn Tokenization End-to-End with Reinforcement Learning

Researchers propose learning tokenization boundaries in large language models using reinforcement learning and score function estimates instead of hardcoded compression. This approach directly optimizes discrete token boundaries, outperforming prior straight-through estimation methods at the 100 million parameter scale.