CMS unveils two more programmes in the Trump administration’s efforts to cut drug prices, which have not been well received by the pharma industry.
Labcorp backs Cellens in developing physics test aimed at bladder cancer
Boston-based company Cellens secured $6.5 million to develop its platform that detects bladder cancer through an approach that combines physics and AI, Endpoints News learned exclusively. Its technology is a departure from the norm in …
Neurocrine’s Ingrezza flunks pivotal study in dyskinetic cerebral palsy
Neurocrine Biosciences’ Ingrezza has failed a late-stage trial in a type of cerebral palsy, adding to a spate of clinical disappointments for the biotech in recent years. Neurocrine did not immediately respond to an …
Pfizer discloses patient death in Hympavzi hemophilia trial
Pfizer said on Monday that a patient in a trial of its hemophilia drug Hympavzi had died after experiencing a cerebellar infarction followed by cerebral hemorrhage. In a letter to hemophilia …
Novo Nordisk gets FDA okay for Wegovy pill
The FDA has delivered a gift to Novo Nordisk ahead of the holiday season, with the prompt approval of its Wegovy pill.
How social media encourages the worst of AI boosterism
Demis Hassabis, CEO of Google DeepMind, summed it up in three words: “This is embarrassing.” Hassabis was replying on X to an overexcited post by Sébastien Bubeck, a research scientist at the rival firm OpenAI, announcing that two mathematicians had used OpenAI’s latest large language model, GPT-5, to find solutions to 10 unsolved problems in […]
CodeGEMM: A Codebook-Centric Approach to Efficient GEMM in Quantized LLMs
arXiv:2512.17970v1 Announce Type: cross Abstract: Weight-only quantization is widely used to mitigate the memory-bound nature of LLM inference. Codebook-based methods extend this trend by achieving strong accuracy in the extremely low-bit regime (e.g., 2-bit). However, current kernels rely on dequantization, which repeatedly fetches centroids and reconstructs weights, incurring substantial latency and cache pressure. We present […]
MixFlow Training: Alleviating Exposure Bias with Slowed Interpolation Mixture
arXiv:2512.19311v1 Announce Type: cross Abstract: This paper studies the training-testing discrepancy (a.k.a. exposure bias) problem for improving the diffusion models. During training, the input of a prediction network at one training timestep is the corresponding ground-truth noisy data that is an interpolation of the noise and the data, and during testing, the input is the […]
R-GenIMA: Integrating Neuroimaging and Genetics with Interpretable Multimodal AI for Alzheimer’s Disease Progression
arXiv:2512.18986v1 Announce Type: cross Abstract: Early detection of Alzheimer’s disease (AD) requires models capable of integrating macro-scale neuroanatomical alterations with micro-scale genetic susceptibility, yet existing multimodal approaches struggle to align these heterogeneous signals. We introduce R-GenIMA, an interpretable multimodal large language model that couples a novel ROI-wise vision transformer with genetic prompting to jointly model […]
Love, Lies, and Language Models: Investigating AI’s Role in Romance-Baiting Scams
arXiv:2512.16280v2 Announce Type: replace-cross Abstract: Romance-baiting scams have become a major source of financial and emotional harm worldwide. These operations are run by organized crime syndicates that traffic thousands of people into forced labor, requiring them to build emotional intimacy with victims over weeks of text conversations before pressuring them into fraudulent cryptocurrency investments. Because […]