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CoDex enables robots to autonomously master complex manipulation tasks without any human demonstrations, achieving dexterity previously thought unattainable.
AI coding agents are reshaping open-source ecosystems by diluting human participation while increasing the burden on code review processes.
Multi-level modelling slashes post-change inconsistencies by unifying artefacts, outperforming traditional two-level modelling in software maintenance scenarios.
Few-shot prompting boosts syntactic quality of LLM-generated model transformation languages, but semantic correctness remains a challenge.
Bounded Context violations in DDD projects are shown to significantly hinder maintenance quality, revealing a critical challenge for practitioners.
LLM agents struggle in dynamic environments, but EvoMem boosts their performance by capturing the evolution of memory, leading to better adaptability.
