1 citations · 1 across the 3 of their papers we have counts for
3 papers
MLIP Detective: Active Failure Mode Discovery Beyond Benchmark Scores for Machine-Learning Interatomic Potentials
Ryuhei Okuno, Nontawat Charoenphakdee, Kaoru Hisama +1
Universal machine-learning interatomic potentials (u-MLIPs) aim to generalize across diverse configurations. Benchmarks enable reproducible evaluation but may not expose failures o…
PARC: An Autonomous Self-Reflective Coding Agent for Robust Execution of Long-Horizon Tasks
Yuki Orimo, Iori Kurata, Hodaka Mori +3
We introduce PARC, a coding agent for the autonomous and robust execution of long-horizon computational tasks. PARC is built on a hierarchical multi-agent architecture incorporatin…
LightPFP: A Lightweight Route to Ab Initio Accuracy at Scale
Wenwen Li, Nontawat Charoenphakdee, Yong-Bin Zhuang +6
Machine learning interatomic potentials (MLIPs) bridge the gap between quantum-mechanical accuracy and scalable molecular simulations. However, a fundamental trade-off persists: un…