Work Force

Cortical maps diverge, representations converge along cortical hierarchy

Brain maps (e.g. retinotopy, somatotopy) vary across individuals. This is thought to reflect underlying computational differences. However, artificial neural networks (ANNs) show that similar performance and internal representations can coexist with diverse circuit layouts. Consequently, we tested the presumption that spatial diversity reflects representational diversity in the brain, but found th...

IndicFairFace: Balanced Indian Face Dataset for Auditing and Mitigating Geographical Bias in Vision-Language Models

Vision-Language Models (VLMs) are known to inherit and amplify societal biases from their web-scale training data with Indian being particularly misrepresented. Existing fairness-aware datasets have significantly improved demographic balance across global race and gender groups, yet they continue to treat Indian as a single monolithic category. The oversimplification ignores the vast intra-nationa...

Amortized Reasoning Tree Search: Decoupling Proposal and Decision in Large Language Models

Reinforcement Learning with Verifiable Rewards (RLVR) has established itself as the dominant paradigm for instilling rigorous reasoning capabilities i...

Beyond Benchmarks of IUGC: Rethinking Requirements of Deep Learning Methods for Intrapartum Ultrasound Biometry from Fetal Ultrasound Videos

A substantial proportion (45\%) of maternal deaths, neonatal deaths, and stillbirths occur during the intrapartum phase, with a particularly high burd...

A spectral framework for measuring diversity in multiple sequence alignments

Machine learning (ML) methods for proteins and RNAs rely on multiple sequence alignments (MSAs) and related datasets such as experimental mutagenesis ...

Spectral-Spatial Contrastive Learning Framework for Regression on Hyperspectral Data

Contrastive learning has demonstrated great success in representation learning, especially for image classification tasks. However, there is still a s...

Vendi Novelty Scores for Out-of-Distribution Detection

Out-of-distribution (OOD) detection is critical for the safe deployment of machine learning systems. Existing post-hoc detectors typically rely on mod...

Multimodal Learning for Arcing Detection in Pantograph-Catenary Systems

The pantograph-catenary interface is essential for ensuring uninterrupted and reliable power delivery in electrified rail systems. However, electrical...

Safety and Utility of an Agentic Large Language Model-Based Hospital Course Summarizer: A Prospective Real-World Pilot Study

Importance: High-quality discharge summaries are essential for safe care transitions but contribute substantially to clinician documentation burden an...

Multi-Scale Global-Instance Prompt Tuning for Continual Test-time Adaptation in Medical Image Segmentation

Distribution shift is a common challenge in medical images obtained from different clinical centers, significantly hindering the deployment of pre-tra...

Diversity-Preserved Distribution Matching Distillation for Fast Visual Synthesis

Distribution matching distillation (DMD) aligns a multi-step generator with its few-step counterpart to enable high-quality generation under low infer...

STEER: Inference-Time Risk Control via Constrained Quality-Diversity Search

Large Language Models (LLMs) trained for average correctness often exhibit mode collapse, producing narrow decision behaviors on tasks where multiple ...

Socially Grounded Exemplars Improve Synthetic Conversations for Health-Related Social Needs Navigation

Health-Related Social Needs (HRSNs) significantly impact health outcomes, yet traditional care often fails to address them effectively. While conversa...

Lung Nodule Image Synthesis Driven by Two-Stage Generative Adversarial Networks

The limited sample size and insufficient diversity of lung nodule CT datasets severely restrict the performance and generalization ability of detectio...

Diversity of antibiotic resistance genes increases in urbanized lakes: a multi-tool screening

Antimicrobial resistance (AMR) is a growing global public health threat projected to cause up to 10 million deaths annually by 2050 if no immediate ac...

MoE-ACT: Improving Surgical Imitation Learning Policies through Supervised Mixture-of-Experts

Imitation learning has achieved remarkable success in robotic manipulation, yet its application to surgical robotics remains challenging due to data s...

BLENDER: Blended Text Embeddings and Diffusion Residuals for Intra-Class Image Synthesis in Deep Metric Learning

The rise of Deep Generative Models (DGM) has enabled the generation of high-quality synthetic data. When used to augment authentic data in Deep Metric...

Deep Learning-Based Spatial Immunoprofiling of Multiplex Immunofluorescence Images Distinguishes Tuberculosis Disease States in Diversity Outbred Mice

Tuberculosis (TB), caused by Mycobacterium tuberculosis (M.tb), remains a major global health challenge, with approximately 10.8 million new cases and...

Transcriptomic profiling reveals neurophysiological gene candidates underlying vocal evolution in African clawed frogs

Neurophysiologists have discovered many mechanisms underlying the production of animal behaviors in specific species; these involve a collection of ne...

From Cold Start to Active Learning: Embedding-Based Scan Selection for Medical Image Segmentation

Accurate segmentation annotations are critical for disease monitoring, yet manual labeling remains a major bottleneck due to the time and expertise re...