Illumina and PREMIA partner to expand clinical access to CGP in Asia
Illumina Taiwan Biotechnology Co., Ltd., and Precision Medicine Asia, Limited (PREMIA), a leading Asian cancer clinical-genomic screening network, today announced the formation of a strategic partnership that will expand access to comprehensive genomic profiling (CGP) for all eligible oncology patie...
Community-driven initiative provides a foundation for collaborative, extensible data platforms Percona, a leader in enterprise-grade open source database software, support, and services, today announced the transition of Percona Everest into an independent open source project called OpenEverest, the...
The platform surpasses 1,100 clinics and 900,000 patients, delivering up to 80% reduction in processing time. Murj®, a cardiac device management software company, today announced record year-over-year growth for the third consecutive year. The company software is now being used by more than 1,100 cl...
Informatica Leads 2026 Gartner MQ for Data & Analytics Platforms
Informatica from Salesforce, a leader in enterprise AI-powered cloud data management, today announced it has been named a Leader in the Gartner® Magic Quadrant™ for Data and Analytics Governance Platforms. The evaluation was based on criteria which analyzed the company’s overall Completeness of Visi...
Amera IoT’s Breakthrough in Quantum-Proof Encryption with 14 U.S. Patents
Amera IoT, a cybersecurity innovator, today announced a major breakthrough in quantum-proof encryption with the launch of AmeraKey® Encryption, a patented technology designed to secure digital communications against both current and future computing threats, including quantum computing. AmeraKey Enc...
Tidal Cyber Appoints Jessica Hall as Vice President of Product
Appointment supports rapid platform expansion and continued innovation in Threat-Led Defense Tidal Cyber, the creator of the Threat-Led Defense category, today announced the appointment of Jessica Hall as Vice President of Product. Hall will lead product development and execution as the company acce...
MoEBlaze: Breaking the Memory Wall for Efficient MoE Training on Modern GPUs
arXiv:2601.05296v1 Announce Type: new
Abstract: The pervasive "memory wall" bottleneck is significantly amplified in modern large-scale Mixture-of-Experts (MoE) architectures. MoE's inherent architectural sparsity leads to sparse arithmetic compute and also introduces substantial activation memory ...
TIME: Temporally Intelligent Meta-reasoning Engine for Context Triggered Explicit Reasoning
arXiv:2601.05300v1 Announce Type: new
Abstract: Reasoning oriented large language models often expose explicit "thinking" as long, turn-global traces at the start of every response, either always on or toggled externally at inference time. While useful for arithmetic, programming, and problem solvi...
Ontology Neural Networks for Topologically Conditioned Constraint Satisfaction
arXiv:2601.05304v1 Announce Type: new
Abstract: Neuro-symbolic reasoning systems face fundamental challenges in maintaining semantic coherence while satisfying physical and logical constraints. Building upon our previous work on Ontology Neural Networks, we present an enhanced framework that integr...
When the Server Steps In: Calibrated Updates for Fair Federated Learning
arXiv:2601.05352v1 Announce Type: new
Abstract: Federated learning (FL) has emerged as a transformative distributed learning paradigm, enabling multiple clients to collaboratively train a global model under the coordination of a central server without sharing their raw training data. While FL offer...
GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting
arXiv:2601.05353v1 Announce Type: new
Abstract: Accurate forecasting of blood glucose from CGM is essential for preventing dysglycemic events, thus enabling proactive diabetes management. However, current forecasting models treat blood glucose readings captured using CGMs as a numerical sequence, e...
Naiad: Novel Agentic Intelligent Autonomous System for Inland Water Monitoring
arXiv:2601.05256v1 Announce Type: new
Abstract: Inland water monitoring is vital for safeguarding public health and ecosystems, enabling timely interventions to mitigate risks. Existing methods often address isolated sub-problems such as cyanobacteria, chlorophyll, or other quality indicators separ...
Mathematical Knowledge Graph-Driven Framework for Equation-Based Predictive and Reliable Additive Manufacturing
arXiv:2601.05298v1 Announce Type: new
Abstract: Additive manufacturing (AM) relies critically on understanding and extrapolating process-property relationships; however, existing data-driven approaches remain limited by fragmented knowledge representations and unreliable extrapolation under sparse ...
Effects of personality steering on cooperative behavior in Large Language Model agents
arXiv:2601.05302v1 Announce Type: new
Abstract: Large language models (LLMs) are increasingly used as autonomous agents in strategic and social interactions. Although recent studies suggest that assigning personality traits to LLMs can influence their behavior, how personality steering affects coop...
Improving Enzyme Prediction with Chemical Reaction Equations by Hypergraph-Enhanced Knowledge Graph Embeddings
arXiv:2601.05330v1 Announce Type: new
Abstract: Predicting enzyme-substrate interactions has long been a fundamental problem in biochemistry and metabolic engineering. While existing methods could leverage databases of expert-curated enzyme-substrate pairs for models to learn from known pair intera...
The Persona Paradox: Medical Personas as Behavioral Priors in Clinical Language Models
arXiv:2601.05376v1 Announce Type: new
Abstract: Persona conditioning can be viewed as a behavioral prior for large language models (LLMs) and is often assumed to confer expertise and improve safety in a monotonic manner. However, its effects on high-stakes clinical decision-making remain poorly cha...
MoEs Are Stronger than You Think: Hyper-Parallel Inference Scaling with RoE
The generation quality of large language models (LLMs) is often improved by utilizing inference-time sequence-level scaling methods (e.g., Chain-of-Thought). We introduce hyper-parallel scaling, a complementary framework that improves prediction quality at the token level. Hyper-parallel scaling com...
Multivariate Conformal Prediction using Optimal Transport
Conformal prediction (CP) quantifies the uncertainty of machine learning models by constructing sets of plausible outputs. These sets are constructed by leveraging a so-called conformity score, a quantity computed using the input point of interest, a prediction model, and past observations. CP sets ...
DeepMMSearch-R1: Empowering Multimodal LLMs in Multimodal Web Search
Multimodal Large Language Models (MLLMs) in real-world applications require access to external knowledge sources and must remain responsive to the dynamic and ever-changing real-world information in order to address information-seeking and knowledge-intensive user queries. Existing approaches, such ...
Over-Searching in Search-Augmented Large Language Models
Search-augmented large language models (LLMs) excel at knowledge-intensive tasks by integrating external retrieval.
However, they often over-search – unnecessarily invoking search tool even when it does not improve response quality,
which leads to computational inefficiency and hallucinations by inc...
Meet SETA: Open Source Training Reinforcement Learning Environments for Terminal Agents with 400 Tasks and CAMEL Toolkit
What does an end to end stack for terminal agents look like when you combine structured toolkits, synthetic RL environments, and benchmark aligned evaluation? A team of researchers from CAMEL AI, Eigent AI and other collaborators have released SETA, a toolkit and environment stack that focuses on re...
Automatic Prompt Optimization for Multimodal Vision Agents: A Self-Driving Car Example
Walkthrough using open-source prompt optimization algorithms in Python to improve the accuracy of an autonomous vehicle car safety agent running on OpenAI's GPT 5.2
The post Automatic Prompt Optimization for Multimodal Vision Agents: A Self-Driving Car Example appeared first on Towards Data Science....