Researchers from the University of Toronto, the Vector Institute, the University of Cambridge, and ServiceNow have built a proof-of-concept computer virus that uses open-weight large language models t…
Bayreuth Festival's new AI-generated staging of Wagner's Ring cycle, curated by German stage director Marcus Lobbes for the festival's 150th anniversary, has been criticized as a 'dismal, mindless mes…
Google launched AI image generation in Google Earth on an unspecified date, allowing users to reimagine real-world locations with prompts, but rolled back the feature within 48 hours after users share…
Alex Stephany, founder and CEO of AI startup Beam, said being fired from his roles as a lawyer and a management consultant before age 30 was the best thing that happened in his career, as it pushed hi…
Oracle has instructed contributors to OpenJDK, the open-source Java project it stewards, not to submit code or other content generated by AI, citing risks to review workloads, safety, security, and in…
South Korea's Kospi index closed 5% lower on Monday, with Samsung Electronics and SK Hynix both falling 9%, after a historic July selloff that left the benchmark roughly a third below its June peak. T…
Researchers propose SAF, a Stable Advantage Fusion framework that combines reinforcement learning with verifiable rewards (RLVR) and on-policy distillation (OPD) for training language models, addressi…
Researchers at an undisclosed institution developed a value-based reinforcement-learning framework using graph neural networks to optimize dynamic matching markets, proving an event-time reduction and…
A new study from arXiv (2607.28908v1) introduces the Human-LLM Reflection Framework (HRF) and finds that large language models (LLMs) fail to improve answers through reflection, showing near-zero info…
Researchers introduced Gated Q-learning, a new algorithm that smoothly interpolates between Watkins' Q(λ) and Peng's Q(λ) to manage off-policy bias in multistep credit assignment for reinforcement lea…
Researchers introduced FairDiffuseVQVAE, a two-stage tabular diffusion model that achieves fairness by construction through uniform sampling of the protected attribute at inference time, decoupling fi…
Researchers propose a computation-efficient method for adversarial training of large language models that cuts per-step FLOPs by 48.1% and requires only 0.0118% trainable parameters compared to standa…
A scoping review of 190 studies on machine learning for surgical risk stratification and outcome prediction using electronic health records found that most relied on single-center private datasets, wi…
Researchers introduced SILVA Networks, a new implicit neural architecture that separates stimulus, local interaction, global interaction, damping, and readout within a fixed-point update, allowing for…
Researchers introduced DFSC, a PyTorch environment for fractional scientific machine learning that uses the Mittag-Leffler Spectral Layer to separate known fractional propagation from data-driven corr…
Researchers introduced implicit machine learning force fields (I-MLFFs) that replace explicit neural network layers with self-consistent fixed-point equations, enabling two- to five-fold reductions in…
Researchers introduced HERO, a program optimizer that uses large language models to generate diverse atomic edits and compose them into coherent improvements, overcoming the weakest-link effect in zer…
Researchers propose new search methods for Branch and Bound (BaB) neural network verification that locate verdict boundaries more efficiently by exploiting path monotonicity and splitting multiple act…
Researchers propose history-enriched rollout training (HERO), a method that augments conventional absolute trajectory supervision with relative supervision derived from the model's optimization histor…
Researchers introduced SERUM, a multi-pass framework that extracts finite-state behavioral models from unstructured egocentric video using hierarchical VLM annotation, achieving lower perplexity and h…