arXiv Machine Learning June 24, 2026 By Krishna Teja Vepa

Computational references are not experiments: pre-registered validation of machine-learned sodium-cathode voltages

Read the original on arXiv Machine Learning →

arXiv:2606. 23725v1 Announce Type: cross Abstract: Machine-learning screens for battery materials are trained and judged almost entirely against computed reference voltages, and those references carry their own systematic errors.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv AI

2d ago

Explanation Multiplicity: Circuit-Level Interpretability Evidence Does Not Survive Defensible Analytic Variation

arXiv:2608. 13754v1 Announce Type: new Abstract: The EU AI Act requires providers of high-risk systems to file technical documentation describing how the system reaches its decisions.

By Ajay Pravin Mahale (Hochschule Trier)

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arXiv AI

Aug 11

When Is Benchmark Contamination Detectable? Information Limits and Power-Calibrated Audits

arXiv:2608. 07914v1 Announce Type: new Abstract: Behavioral contamination detectors can return "no evidence" either because a benchmark is clean or because the audit has little power.

By Ibne Farabi Shihab, Sanjeda Akter, Anuj Sharma

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arXiv Machine Learning

Jul 21

Bridging battery design and health assessment through virtual sensing and physics-informed learning

arXiv:2607. 16864v1 Announce Type: new Abstract: Supercharging of lithium-ion batteries (LiBs) requires robust health monitoring to ensure durability, safety, and user confidence, particularly for emerging vehicle-to-grid applications with bidirectional energy flows.

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arXiv AI

Jul 22

Circuit Claims Depend on What Is Extracted and How It Is Compared

arXiv:2607. 18921v1 Announce Type: cross Abstract: Circuit extraction identifies a small set of model components whose presence preserves a target behavior under ablation, and the resulting circuit is often read as the mechanism behind that behavior.

By Yang Sheng, Jie Fu

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arXiv Machine Learning

1d ago

Quantifying the Gap Between Laboratory Battery Test Patterns and Field Duty Profiles

arXiv:2608. 16212v1 Announce Type: new Abstract: Laboratory battery tests provide the main empirical basis for battery performance and degradation studies, but their operating patterns do not directly represent field duty profiles.

By Chunyang Zhao, Chresten Tr{\ae}holt

arXiv Machine Learning

5d ago

Excess Separability: Nuisance-Controlled Residual-Stream Probing for Benchmark Contamination Detection

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Explanation Multiplicity: Circuit-Level Interpretability Evidence Does Not Survive Defensible Analytic Variation

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