Technology & AI
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.
AI Models
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Technology & AI
Gasp paper proposes bridge-free cross-chain DEX rollup
An arXiv preprint describes Gasp, an L2 rollup DEX using EigenLayer restaking for gas-free cross-chain swaps without traditional bridges.
Technology & AI
Prompt syntax shifts open LLM code security, preprint finds
Prompt syntax changes whether open-source LLMs generate secure or vulnerable code, a new preprint finds, with direct impact on self-hosting teams.
Technology & AI
Byzantine fault tolerance breaks with AI agents, preprint warns
A July 2026 arXiv preprint shows AI agents following every consensus rule can still certify wrong answers, and shared model weights make them fail
Technology & AI
CRAFT method finds why LLMs fail, then fixes them
arXiv preprint CRAFT turns grading rubrics into capability diagnoses, generating targeted fine-tuning data that beats EvalTree on four models.
Technology & AI
ToolVerse trains AI agents across 4500 real-world tools
New arXiv framework auto-builds massive training environments from 400 Model Context Protocols to teach AI agents long-horizon tool use.
Technology & AI
PagedWeight cuts MoE serving memory 72% with FP16 accuracy
A new preprint claims PagedWeight dynamically quantizes MoE model weights at runtime, saving 72% GPU memory and lifting throughput 1.94× for AI inference.
Technology & AI
New framework tests if frontier AI helps plan CBRN attacks
A new arXiv preprint introduces a method to measure whether frontier AI helps non-experts plan CBRN attacks, with uplift limited to radiological threats.
Technology & AI
Knowledgeless AI models cut hallucination, boost evidence use 25%
A new arXiv preprint strips named entities from training data, and the resulting models recall fewer facts but answer questions from context up to 25%
Technology & AI
LoRA cascaded fusion preprint targets medical training AI
LoRA cascaded fusion preprint proposes adding AI input modalities one at a time for nurse training action recognition, without full retraining.
Technology & AI
LLM accuracy hides prediction flips from irrelevant context
arXiv research from Georgia Tech and Stanford shows language models flip individual answers when fed meaningless text, as overall scores hold steady.
Technology & AI
EVOQUANT lifts trading Sharpe from -0.30 to 0.54
An arXiv paper uses LLMs with a multi-stage verifier to fix losing quantitative trading strategies, lifting average Sharpe from -0.298 to 0.538.