Corcept shares surge on FDA approval of Lifyorli, a first-in-class selective glucocorticoid receptor antagonist for ovarian cancer.
FDA clears Denali’s ‘game-changer’ Hunter syndrome drug
Denali’s Avlayah is the first drug for neurological complications associated Hunter syndrome to be approved in the US.
Shaping the future of multiple myeloma with artificial intelligence and digital twins: from concept to clinic
Multiple myeloma (MM) is an incurable hematological malignancy with significant clinical and biological heterogeneity. Despite development and refinement of numerous prognostic models for MM, challenges with accurate and reliable risk stratification remain, highlighted by unexpected, early relapse or progression of disease in patients termed functional high-risk (FHR). To improve decision-making and optimise outcome, there is […]
Ontology- and LLM-based data harmonization for federated learning in healthcare
IntroductionSemantic heterogeneity across electronic health records (EHRs) limits scalable and privacy-preserving analytics in healthcare. While federated learning (FL) enables collaborative modeling without sharing raw data, it requires consistent, ontology-aligned representations. We present an ontology- and large language model (LLM)-based data harmonization approach to support secure, interoperable FL workflows.MethodsWe propose a general two-step pipeline for converting […]
A pre-treatment comparison of referral pathways to guided ICBT for depression and anxiety disorders – A naturalistic study in routine clinical care
IntroductionSelf-referral to therapist-guided internet-delivered cognitive behavioral therapy (guided ICBT) is increasingly being implemented in specialized mental healthcare settings to reduce barriers to care. Little is known about the characteristics of patients who access treatment through this pathway compared to the traditional referral pathway from general practitioner (GP). This study aims to compare demographic characteristics, socioeconomic […]
Enhancing Efficiency and Performance in Deepfake Audio Detection through Neuron-level dropin & Neuroplasticity Mechanisms
arXiv:2603.24343v1 Announce Type: cross Abstract: Current audio deepfake detection has achieved remarkable performance using diverse deep learning architectures such as ResNet, and has seen further improvements with the introduction of large models (LMs) like Wav2Vec. The success of large language models (LLMs) further demonstrates the benefits of scaling model parameters, but also highlights one bottleneck […]
A Sociolinguistic Analysis of Automatic Speech Recognition Bias in Newcastle English
arXiv:2603.24549v1 Announce Type: cross Abstract: Automatic Speech Recognition (ASR) systems are widely used in everyday communication, education, healthcare, and industry, yet their performance remains uneven across speakers, particularly when dialectal variation diverges from the mainstream accents represented in training data. This study investigates ASR bias through a sociolinguistic analysis of Newcastle English, a regional variety […]
Bottlenecked Transformers: Periodic KV Cache Consolidation for Generalised Reasoning
arXiv:2505.16950v4 Announce Type: replace-cross Abstract: Transformer LLMs have been shown to exhibit strong reasoning ability that scales with inference-time compute, most prominently through token-space “thinking” chains of thought. A growing line of work pushes extra computation into the model’s latent space, which we term Auxiliary Latent-Space Computation (ALSC). Existing ALSC methods largely fall into three […]
The Alignment Tax: Response Homogenization in Aligned LLMs and Its Implications for Uncertainty Estimation
arXiv:2603.24124v1 Announce Type: cross Abstract: RLHF-aligned language models exhibit response homogenization: on TruthfulQA (n=790), 40-79% of questions produce a single semantic cluster across 10 i.i.d. samples. On affected questions, sampling-based uncertainty methods have zero discriminative power (AUROC=0.500), while free token entropy retains signal (0.603). This alignment tax is task-dependent: on GSM8K (n=500), token entropy achieves […]
Upper Entropy for 2-Monotone Lower Probabilities
arXiv:2603.23558v1 Announce Type: cross Abstract: Uncertainty quantification is a key aspect in many tasks such as model selection/regularization, or quantifying prediction uncertainties to perform active learning or OOD detection. Within credal approaches that consider modeling uncertainty as probability sets, upper entropy plays a central role as an uncertainty measure. This paper is devoted to the […]
Assessment Design in the AI Era: A Method for Identifying Items Functioning Differentially for Humans and Chatbots
arXiv:2603.23682v1 Announce Type: cross Abstract: The rapid adoption of large language models (LLMs) in education raises profound challenges for assessment design. To adapt assessments to the presence of LLM-based tools, it is crucial to characterize the strengths and weaknesses of LLMs in a generalizable, valid and reliable manner. However, current LLM evaluations often rely on […]
Toward Generalist Neural Motion Planners for Robotic Manipulators: Challenges and Opportunities
arXiv:2603.24318v1 Announce Type: cross Abstract: State-of-the-art generalist manipulation policies have enabled the deployment of robotic manipulators in unstructured human environments. However, these frameworks struggle in cluttered environments primarily because they utilize auxiliary modules for low-level motion planning and control. Motion planning remains challenging due to the high dimensionality of the robot’s configuration space and the […]