MLSys 2025 Call For Papers

Authors are encouraged to submit previously unpublished research at the intersection of machine learning and computer systems. The MLSys Program Committee will select papers based on a combination of novelty, quality, interest, and impact.

Topics of interest cover both systems for machine learning and machine learning for systems, and include, but are not limited to:

• Efficient model training, inference, and serving

• Large language model (LLM) training, fine-tuning, and inference 

• Compound AI systems and AI agent systems

• Distributed and federated learning algorithms

• Privacy and security for ML applications

• ML methods for job scheduling in computing systems

• Testing, debugging, and monitoring of ML applications

• Fairness, interpretability, and explainability for ML applications

• Data preparation and data cleaning

• ML programming models and abstractions

• Programming languages for machine learning

• ML compilers and runtimes

• Visualization of data, models, and predictions

• Specialized hardware for machine learning

• LLM-based hardware design or system optimization techniques 

• Hardware-efficient ML methods

• Machine learning benchmarks, datasets, and tooling