The AI knowledge 99.9% of people never discover
A July 2026 arXiv paper proposes a semantic framework that names six ways AI systems misrepresent reality, aiming to replace fluency with verifiable
A new arXiv survey maps how LLMs could move front-end chip design from isolated tasks to autonomous agents, but offers no benchmarks to prove it works.
A new arXiv preprint proposes a training-free method that helps language models actually use evidence already sitting inside their 128K-token context
LLM-as-a-Verifier treats checking AI answers as a scaling axis, hitting 86.5% on Terminal-Bench V2 and 78.2% on SWE-Bench Verified without extra training.
VAORA, a new reward design on arXiv, targets hallucinated reasoning and reasoning-action misalignment in vision-language models on physical tasks.
A new arXiv preprint from IIT Madras proposes a blockchain-verifiable voting system on Solana that keeps ballots private without a trusted key dealer
Limited quantum memory collapses the gap between stabilizer testing and learning, a new arXiv preprint shows, with both needing Theta(n) copies.
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.
