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cs.SE2026
CRRL: A Causality-Based Reinforcement Learning Framework for Autonomous System Recovery
Safia Fatima, Kai Olav Ellefsen, Leon Moonen
Traditional reinforcement learning (RL) for recovery in autonomous systems lacks causal understanding and generalizes poorly to novel failure scenarios. RL policies often stall in…
cs.SE2026
Smaller Models, Unexpected Costs: Trade-offs in LLM Quantization for Automated Program Repair
Fernando Vallecillos-Ruiz, Giordano d'Aloisio, Max Hort +3
Large Language Models (LLMs) are powerful tools and have been increasingly adopted for complex software engineering tasks. As the number of parameters increases, results can often…