{"total":20,"rows":[{"id":"2510.06189","title":"Barbarians at the Gate: How AI is Upending Systems Research","created":"2025-10-07","cited_by_count":54,"area":null},{"id":"2602.02919","title":"DeltaEvolve: Accelerating Scientific Discovery through Momentum-Driven Evolution","created":"2026-02-02","cited_by_count":26,"area":null},{"id":"2606.11926","title":"Toward Generalist Autonomous Research via Hypothesis-Tree Refinement","created":"2026-06-10","cited_by_count":22,"area":null},{"id":"2511.06090","title":"SWE-fficiency: Can Language Models Optimize Real-World Repositories on Real Workloads?","created":"2025-11-08","cited_by_count":21,"area":null},{"id":"2604.19341","title":"Structured Scaling of AI Discovery Across Diverse Scientific Domains","created":"2026-04-21","cited_by_count":21,"area":null},{"id":"2605.08678","title":"MLS-Bench: A Holistic and Rigorous Assessment of AI Systems on Building Better AI","created":"2026-05-09","cited_by_count":17,"area":null},{"id":"2510.27176","title":"Glia: A Human-Inspired AI for Automated Systems Design and Optimization","created":"2025-10-31","cited_by_count":16,"area":null},{"id":"2511.07262","title":"AgenticSciML: Collaborative Multi-Agent Systems for Emergent Discovery in Scientific Machine Learning","created":"2025-11-10","cited_by_count":14,"area":null},{"id":"2603.13428","title":"SWE-Milestone: Evaluating AI Agents on Continuous Software Evolution","created":"2026-03-13","cited_by_count":8,"area":null},{"id":"2603.23994","title":"Understanding the Challenges in Iterative Generative Optimization with LLMs","created":"2026-03-25","cited_by_count":8,"area":null},{"id":"2606.29082","title":"Evolution Fine-Tuning: Learning to Discover Across 371 Optimization Tasks","created":"2026-06-27","cited_by_count":6,"area":null},{"id":"2607.19653","title":"PerfAgent: Profiler-Guided Iterative Refinement for Repository-Level Code Optimization","created":"2026-07-22","cited_by_count":3,"area":null},{"id":"2512.14806","title":"Let the Barbarians In: How AI Can Accelerate Systems Performance Research","created":"2025-12-16","cited_by_count":2,"area":null},{"id":"2605.15308","title":"SMCEvolve: Principled Scientific Discovery via Sequential Monte Carlo Evolution","created":"2026-05-14","cited_by_count":2,"area":null},{"id":"2607.25090","title":"Matryoshka Agent: Unfolding Sub-Agents for Long-Horizon Machine Learning Engineering","created":"2026-07-27","cited_by_count":2,"area":null},{"id":"2603.13640","title":"SemRep: Generative Code Representation Learning with Code Transformations","created":"2026-03-13","cited_by_count":0,"area":null},{"id":"2605.18004","title":"RL4RLA: Teaching ML to Discover Randomized Linear Algebra Algorithms Through Curriculum Design and Graph-Based Search","created":"2026-05-18","cited_by_count":0,"area":null},{"id":"2606.01975","title":"Algorithmic algorithm development with LLMs: A Case Study on LLM-Usage for Contraction Order Optimization in Tensor Networks","created":"2026-06-01","cited_by_count":0,"area":null},{"id":"2606.07527","title":"Post-training is (Massive) Supervised Learning","created":"2026-04-20","cited_by_count":0,"area":null},{"id":"2609.37849","title":"Is manual software optimization a thing of the past?","created":"2026-09-29","cited_by_count":0,"area":null}],"next_cursor":null}