Ciencias de la vida

Navigating Gigapixel Pathology Images with Large Multimodal Models

- Recent advances in large multimodal models have allowed for the development of interactive chat models that can converse and reason about pathology whole-slide images (WSIs). However, existing...

Enhancing Energy and Spectral Efficiency in IoT-Cellular Networks via Active SIM-Equipped LEO Satellites

- This paper investigates a low Earth orbit (LEO) satellite communication system enhanced by an active stacked intelligent metasurface (ASIM), mounted on the backplate of the satellite solar panels to...

GetNetUPAM: Ecologically Informed Nested Cross-Validation and Noise-Robust Attention for Marine Bioacoustic Monitoring

- Deploying reliable bioacoustic monitoring systems requires models that generalize under high-noise, low-SNR conditions and evaluation protocols that expose deployment-relevant failure modes, gaps...

Metriplectic Conditional Flow Matching for Dissipative Dynamics

- Metriplectic conditional flow matching (MCFM) learns dissipative dynamics without violating first principles. Neural surrogates often inject energy and destabilize long-horizon rollouts; MCFM instead...

Retrieval-Augmented Foundation Models for Water Level Prediction in the Everglades

- Accurate water level forecasting in the Everglades is essential for flood mitigation, drought management, water resource planning, and biodiversity conservation. While recent time-series foundation...

Modality-Aware Feature Matching in Visual and Vision-Language Applications: A Comprehensive Survey

- Feature matching is a cornerstone task in computer vision, essential for applications such as image retrieval, stereo matching, 3D reconstruction, and SLAM. This survey comprehensively reviews...

Simply-typed constant-domain modal lambda calculus I: distanced beta reduction and combinatory logic

- A system $\boldsymbol\lambda_{\theta}$ is developed that combines modal logic and simply-typed lambda calculus, and that generalizes the system studied by Montague and Gallin. Whereas Montague and...

Oncomorphic neural agent populations for resource-limited sequential learning

- Distributed artificial intelligence (AI) often operates under sequential task exposure, uneven compute, and decentralized coordination. Here, we present a cancer-inspired, or oncomorphic, multi-agent...

Lightweight and Interpretable Transformer via Mixed Graph Algorithm Unrolling for Traffic Forecast

- Unlike conventional "black-box" transformers with classical self-attention mechanism, we build a lightweight and interpretable transformer-like neural net by unrolling a mixed-graph-based...

Valid Inference with Synthetic Data via Task Exchangeability

- There is a proliferation of work arguing for the use of synthetic data in scientific research. For example, social scientists are arguing for the use of LLM-generated "silicon samples" in...

Improving Robotic Generalist Policies via Flow Reversal Steering

- Generalist policies can learn a wide range of skills from diverse robot datasets. In order to solve or improve on challenging news tasks, we need a way to infer and invoke the appropriate actions...

Estimating Individualized Treatment Effects in Acute Ischemic Stroke with Causal Transformation Models (TRAM-DAG): A Multi-Centre Observational Study with External RCT Validation

- Personalized medicine in acute ischemic stroke requires moving beyond average treatment effects (ATE) to individualized treatment effect (ITE) estimates to support treatment decisions. In acute...

OCOO-T : A Simple and Scalable Virtual Cell Model for Transcriptional Perturbation Response Prediction

- Predicting single-cell transcriptional responses to genetic, chemical and cytokine perturbations is a fundamental challenge in computational biology and AI Virtual Cell (AIVC) modeling, with direct...

The Tone of Awareness: Topic, Sentiment, and Toxicity Maps During Mental Health Month on TikTok

- Despite raising concerns about the mental health effects associated with the usage of TikTok, little is known about how related content is framed by creators and received by audiences. We collect the...

Towards Effective Waste Segmentation for Automated Waste Recycling in Cluttered Background

- Rapid expansion of urban areas and population growth is causing an immense increase in waste production, which demands the need for efficient and automated waste management. In this scenario,...

Is It You or Your Environment? A Bayesian Inference Framework for Genomically-Anchored Personalized Physiological Interpretation

- Personalized health AI systems face a fundamental cold-start problem: machine learning models for physiological interpretation require weeks of individual behavioral data before they can distinguish...

ReSCom: A Reconfigurable Spiking Neural Network Accelerator Using Stochastic Computing

- Spiking Neural Networks (SNNs) provide an attractive framework for energy-efficient inference due to their event-driven computation and biologically inspired dynamics. However, efficient hardware...

Finding Conservation Laws of Large Dynamical Systems with Tasks and Futures: A Case Study in Utilizing Dynamic Data Dependencies

- As parallel workloads grow in complexity, managing fine-grained data dependencies becomes a critical challenge. Futures offer a promising model for handling these dependencies, particularly in...

ArogyaSutra: A Multi-Agent Framework for Multimodal Medical Reasoning in Indic Languages

- Multimodal Large Language Models (MLLMs) have shown promising reasoning capabilities in general domains, yet their performance remains limited in specialized settings such as healthcare, especially...

Ride, Track, and Recover: Pilot Randomized Trial of a Wearable Digital Self-Management Intervention During a Veteran Endurance-Cycling Program

- Post-traumatic stress disorder (PTSD) in veterans is characterized by persistent hyperarousal and comorbid anxiety and depressive symptoms that are difficult to monitor and manage outside clinical...

SupraSNN: Exploiting Synapse-Level Parallelism in Spiking Neural Network Accelerators through Co-Optimized Mapping and Scheduling

- Spiking Neural Networks (SNNs) offer a brain-inspired path toward highly efficient computation, but their practical deployment is constrained by the challenge of managing and executing their massive...