As cell and gene therapies with high price tags become more prevalent, a new startup is aiming to help employers and health plans navigate those costs in a more predictable way. The New York-based startup …
ASH: Jaypirca matches Imbruvica in first-line CLL trial
Eli Lilly has revealed the data it hopes will take BTK inhibitor Jaypirca into frontline use for chronic lymphocytic leukaemia.
ASH: FDA okays Gamida aplastic anaemia therapy as data drops
The first cell therapy for severe aplastic anaemia – Gamida Cell’s Omisirge – has been approved by the FDA.
With eye on AI, Imre hires Nadine Lafond from Ogilvy Health to fill CEO vacancy
Ad agency Imre has filled the vacancy at the top of its organization, poaching Nadine Lafond from Ogilvy to serve as its CEO.
Real-time digital monitoring of continuous bladder irrigation: clinical evaluation of a sensor-based system for hematuria and catheter-associated events
IntroductionContinuous bladder irrigation (CBI) is commonly applied after transurethral resection of the prostate (TURP) or bladder tumor (TURBT) to prevent clot formation and maintain catheter patency. Despite its widespread use, the monitoring of CBI remains largely manual and subjective, relying on intermittent visual inspection of outflow characteristics. This approach is labor-intensive, prone to inter-observer variability, […]
Instance Dependent Testing of Samplers using Interval Conditioning
arXiv:2512.06458v1 Announce Type: cross Abstract: Sampling algorithms play a pivotal role in probabilistic AI. However, verifying if a sampler program indeed samples from the claimed distribution is a notoriously hard problem. Provably correct testers like Barbarik, Teq, Flash, CubeProbe for testing of different kinds of samplers were proposed only in the last few years. All […]
Towards Efficient Hypergraph and Multi-LLM Agent Recommender Systems
arXiv:2512.06590v1 Announce Type: cross Abstract: Recommender Systems (RSs) have become the cornerstone of various applications such as e-commerce and social media platforms. The evolution of RSs is paramount in the digital era, in which personalised user experience is tailored to the user’s preferences. Large Language Models (LLMs) have sparked a new paradigm – generative retrieval […]
TV2TV: A Unified Framework for Interleaved Language and Video Generation
arXiv:2512.05103v2 Announce Type: replace-cross Abstract: Video generation models are rapidly advancing, but can still struggle with complex video outputs that require significant semantic branching or repeated high-level reasoning about what should happen next. In this paper, we introduce a new class of omni video-text models that integrate ideas from recent LM reasoning advances to address […]
Venus: An Efficient Edge Memory-and-Retrieval System for VLM-based Online Video Understanding
arXiv:2512.07344v1 Announce Type: cross Abstract: Vision-language models (VLMs) have demonstrated impressive multimodal comprehension capabilities and are being deployed in an increasing number of online video understanding applications. While recent efforts extensively explore advancing VLMs’ reasoning power in these cases, deployment constraints are overlooked, leading to overwhelming system overhead in real-world deployments. To address that, we […]
DeepAgent: A Dual Stream Multi Agent Fusion for Robust Multimodal Deepfake Detection
arXiv:2512.07351v1 Announce Type: cross Abstract: The increasing use of synthetic media, particularly deepfakes, is an emerging challenge for digital content verification. Although recent studies use both audio and visual information, most integrate these cues within a single model, which remains vulnerable to modality mismatches, noise, and manipulation. To address this gap, we propose DeepAgent, an […]