AI vision models encode correct count but output wrong numbers
Vision-language models internally encode the right answer but misread it, a new arXiv study finds. A simple fix lifts counting accuracy 15.6 points.
The AI knowledge 99.9% of people never discover
AI model releases and benchmarks — what each new model actually changes for the people who use it.
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Vision-language models internally encode the right answer but misread it, a new arXiv study finds. A simple fix lifts counting accuracy 15.6 points.
Spotify and Queen Mary researchers found voice features like tone and pace correlate with audiobook engagement even after controlling for the title.
A new arXiv preprint introduces Dynamic Fréchet Regression, predicting full probability distributions across an index and selecting driving features.
New 5,620-case benchmark finds frontier AI matches physicians on positive clinical steps but triggers more unsafe responses in real consultations.
New DFKI preprint argues AI in pre-demolition audits must prioritise defensible decisions over accuracy, proposing four knowledge-graph modes.
Physics-constrained ML encodes the second law of thermodynamics into a combustion surrogate, cutting simulation costs by more than 10x.
LDT-Coord uses a lightweight digital twin to coordinate teams of LLM-powered robots, matching conventional methods at a fraction of the chatter.
Malaika, a multi-agent AI framework posted to arXiv this month, uses three grounding mechanisms to make malware analysis more precise and auditable.
TrustX ARC, a new arXiv preprint, scores agentic AI risk across 12 dimensions into three governance tiers for risk officers, developers and regulators.
A new arXiv preprint pairs an LLM planner with a forecasting model to guard industrial control systems, recording zero hallucinated actions in attack
KV-PRM reads the memory AI models already produce during generation, slashing the cost of verifying multi-agent reasoning chains by up to 5,000x.
New arXiv paper with 489 probes shows structural scaffolding around a fixed LLM cuts failure rates, challenging the bigger-model assumption.