arXiv paper revives rule-based AI for transparency via optimization
A new arXiv survey argues logic plus modern optimization makes rule-based AI practical, offering explainable systems where neural networks fall short.
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A new arXiv survey argues logic plus modern optimization makes rule-based AI practical, offering explainable systems where neural networks fall short.
A July 2026 preprint proposes harmonizing the capability thresholds frontier AI labs publish, which differ so much that no one can verify them.
An arXiv preprint describes Gasp, an L2 rollup DEX using EigenLayer restaking for gas-free cross-chain swaps without traditional bridges.
Prompt syntax changes whether open-source LLMs generate secure or vulnerable code, a new preprint finds, with direct impact on self-hosting teams.
A July 2026 arXiv preprint shows AI agents following every consensus rule can still certify wrong answers, and shared model weights make them fail
arXiv preprint CRAFT turns grading rubrics into capability diagnoses, generating targeted fine-tuning data that beats EvalTree on four models.
SciForge, an open-source AI workbench posted to arXiv on July 20, lets scientists keep judgment while agents handle search, parsing, plotting and writing.
Researchers show a 5G NR side-channel attack can halve a user's video stream quality by reading public scheduling data, without touching encrypted traffic.
New arXiv framework auto-builds massive training environments from 400 Model Context Protocols to teach AI agents long-horizon tool use.
OpenAI's July 2026 safety post details new risks in long-horizon AI models and iterative safeguards, relevant to any business deploying autonomous agents.
NVIDIA's new 4-billion-parameter open model generates 32 robot actions per inference on Jetson Thor, bringing real-time reasoning to edge devices for the
A new preprint claims PagedWeight dynamically quantizes MoE model weights at runtime, saving 72% GPU memory and lifting throughput 1.94× for AI inference.