#incontextlearning

A new method lets robot policies figure out a changed setup from a few seconds of self-directed fiddling, so they keep working when the camera or robot body changes - with no retraining.

How atomic fact accumulation + lookahead search fixes long-horizon LLM agent failures — no fine-tuning required. ICML 2025 paper PoC with measured results.

Key Takeaways Many-shot prompting can significantly improve large language model performance on...