2026
In-Context Learning as Rate–Distortion Optimization
ICML 2026poster
In-context learning (ICL) is a practical way to adapt large models, yet under strict context limits it remains unclear how to spend scarce tokens without being misled by noisy, redundant, or conflicting demonstrations. We address this gap by targeting token-budgeted context construction: how to sele…