Label-free AI sorts real cosmic signals from noise
A new arXiv preprint trains a Real-Bogus classifier without human labels, using simulated injections and dual-network co-teaching for noisy survey data.
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A new arXiv preprint trains a Real-Bogus classifier without human labels, using simulated injections and dual-network co-teaching for noisy survey data.
A new preprint pairs quantum convolutional networks with path signature kernels to tackle reparameterisation invariance in time series classification.
New preprint Orcaella lets clients pick a fast 2-message-delay commit or a resilient path tolerating 54% equivocation at double the latency.
New arXiv preprint from NTU and Alibaba introduces a Vision-Language-Action model needing only a single RGB image to handle unseen camera angles.
Columbia researchers want data infrastructure to do more than store information — they want it to actively keep autonomous agents from causing harm
New arXiv paper shows low-rank adapters can dial up or suppress AI model personality traits like neuroticism and agreeableness, with measurable effects on safet
New preprint cuts encrypted Transformer bootstraps 2.65× with 1.2% perplexity cost, bringing privacy-preserving AI inference closer to practical real-world depl
xDECAF, a browser-based tool checking data flow diagrams against security constraints, shipped as a public preprint with a reusable dataset of over 20 models.
A July 2026 preprint shows VLMs lose localization accuracy in a single forward pass inside diffusion editing pipelines, affecting AI image tool builders and use
FootsiesGym, a July 8 arXiv preprint, turns a minimalist 2D fighting game into an open-source RL benchmark for imperfect-information games that runs on standard
A new arXiv preprint proposes random sampling maps that let models trained on small inputs handle larger ones they never saw — with explicit generalisation rate
World model spatial reasoning scores collapse from 0.90 to 0.27 when the goal is hidden, exposing instruction leakage — a prompt-cheating flaw the authors diagn