3 papers
cs.AI2026
Evaluating Agentic Configuration Repair for Computer Networks
Rufat Asadli, Benjamin Hoffman, Ioannis Protogeros +1
Misconfigurations in computer networks remain a major source of critical Internet outages. Research is turning to Large Language Models (LLMs) to automate the complex, error-prone…
cs.NI2026
Benchmarking LLM-Driven Network Configuration Repair
Ioannis Protogeros, Rufat Asadli, Benjamin Hoffman +1
There is a rapidly growing interest in using Large Language Models (LLMs) to automate complex network operations, but their reliable adoption requires rigorous assessment of their…
cs.CL2025
Towards Developmentally Plausible Rewards: Communicative Success as a Learning Signal for Interactive Language Models
Lennart Stöpler, Rufat Asadli, Mitja Nikolaus +2
We propose a method for training language models in an interactive setting inspired by child language acquisition. In our setting, a speaker attempts to communicate some informatio…