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Do Agent Optimizers Compound? A Continual-Learning Evaluation on Terminal-Bench 2.0
Researchers investigated if improvements made by agent-optimization methods persist when agents are optimized again on new tasks. They found that one method called RELAI-VCL was the only one that both transferred…
DiaLLM: An Investigation into the Robustness-Generation Gap in English Dialect Adaptation
Researchers introduce DiaLLM, a system that aims to address the issue of large language models only producing standard English while understanding dialectal English. The study compares three open-weight language model…
Beyond Adam: SOAP and Muon for Faster, Label-Efficient Training of Machine Learning Interatomic Potentials
The researchers compare the performance of various matrix-structured optimizers (including Muon, SOAP, and SOAP-Muon) to Adam in training machine learning interatomic potentials (MLIPs). They found that these…
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