For every paper on this page, at least one of the original authors has seen our plain-language explanation and engaged with it — either confirming it reads accurately or requesting corrections that we then applied. An endorsement does not mean the authors formally approve every sentence, but it does mean the explanation has passed the eyes of the people who wrote the paper.

951 papers reviewed by authors · 471–480 / 951

💻 computer science

Operationalizing Cyber Attack Prediction: A Gap-Prioritized Framework with Dataset and Model Selection Guidelines

This paper bridges the gap between theoretical research and practical deployment in AI-driven cyber defense by analyzing over 150 datasets and 200 studies to prioritize critical implementation hurdles, introduce a gap-prioritization framework, and provide actionable guidelines for dataset selection and model deployment.

Aminu Muhammad Auwal2026-06-03✓ Author reviewed
💻 computer science

Beyond False Stability: High-Noise Drift Gating for Test-Time Adversarial Defenses in Vision-Language Models

This paper introduces a training-free, plug-in "drift-gating" mechanism that leverages the heightened instability of adversarial examples under high-noise perturbations to selectively trigger test-time defenses, thereby significantly improving the clean-robustness trade-off in Vision-Language Models without degrading clean accuracy.

Hashmat Shadab Malik, Muzammal Naseer, Salman Khan2026-06-03✓ Author reviewed
🤖 machine learning

d2: Improving Reasoning in Diffusion Language Models via Trajectory Likelihood Estimation

The paper introduces d2, a novel reinforcement learning framework for masked diffusion language models that employs specialized trajectory likelihood estimators (d2-AnyOrder and d2-StepMerge) to significantly enhance reasoning capabilities on logical and mathematical benchmarks, achieving new state-of-the-art performance.

Guanghan Wang, Gilad Turok, Yair Schiff, Marianne Arriola, Volodymyr Kuleshov2026-06-02✓ Author reviewed
📈 economics

Hashprice modulates the electricity demand response of Bitcoin miners

This paper demonstrates that Bitcoin miners' electricity demand response to rising costs in the Texas power market is economically state-dependent, becoming weaker as higher "hashprice" (expected mining revenue) shifts the threshold for curtailment to higher electricity prices, thereby suggesting that treating such loads as reliable grid flexibility resources may overstate their actual availability.

Subir Majumder2026-06-02✓ Author reviewed
🔬 physics

Civilizational Metamaterials: Engineering Coordination Under Capability Gradients and Structural Turbulence

This paper proposes a formal engineering framework inspired by metamaterials to model institutional coordination under AI-driven decision velocity, introducing a constitutive law that predicts a catastrophic "Freezing Equilibrium" when verification costs exceed utility and offering testable hypotheses to prevent this phase transition through optimized provenance and verification structures.

David Orban2026-06-02✓ Author reviewed