Health
1353 storiesPublic health and medicine worldwide — sourced from WHO News.
Galerkin-type time discretizations for parabolic and hyperbolic problems: stability and a priori error analysis
arXiv:2601.19828v2 Announce Type: replace Abstract: Galerkin-type time discretizations are variational time-stepping schemes in which the test and trial spaces consist of piecewise polynomials in time. This paper reviews…
Breaking the Reasoning Horizon in Entity Alignment Foundation Models
arXiv:2601.21174v3 Announce Type: replace Abstract: Entity alignment (EA) is critical for knowledge graph (KG) fusion. Existing EA models lack transferability and are incapable of aligning unseen KGs without retraining. …
Think Like a Doctor: Conversational Diagnosis through the Exploration of Diagnostic Knowledge Graphs
arXiv:2602.01995v2 Announce Type: replace Abstract: Conversational diagnosis requires multi-turn history-taking, where an agent asks clarifying questions to refine differential diagnoses under incomplete information. Exi…
MAS-ProVe: Understanding the Process Verification of Multi-Agent Systems
arXiv:2602.03053v2 Announce Type: replace Abstract: Multi-Agent Systems (MAS) built on Large Language Models (LLMs) often exhibit high variance in their reasoning trajectories. Process verification, which evaluates inter…
Beyond Tokens: Semantic-Aware Speculative Decoding for Efficient Inference by Probing Internal States
arXiv:2602.03708v3 Announce Type: replace Abstract: Large Language Models (LLMs) achieve strong performance across many tasks but suffer from high inference latency due to autoregressive decoding. The issue is exacerbate…
Emulating Heterogeneous Client Execution in Federated Learning
arXiv:2602.06498v2 Announce Type: replace Abstract: FL systems are inherently subject to client heterogeneity arising from differences in hardware capabilities. We propose a realistic evaluation framework for hardware-aw…
Term Coding and Dispersion: Exact and Asymptotic Decision Problems
arXiv:2602.08110v2 Announce Type: replace Abstract: Let t be a tuple of r terms that, under an interpretation on an n-element alphabet A, defines a map from k-tuples over A to r-tuples over A. We study the decision theor…
Test vs Mutant: Adversarial LLM Agents for Robust Unit Test Generation
arXiv:2602.08146v3 Announce Type: replace Abstract: Software testing is a critical, yet resource-intensive phase of the software development lifecycle. Over the years, various automated tools have been developed to aid i…
From Legible to Inscrutable Trajectories: (Il)legible Motion Planning Accounting for Multiple Observers
arXiv:2602.09227v2 Announce Type: replace Abstract: In cooperative environments, such as in factories or assistive scenarios, it is important for a robot to communicate its intentions to observers, who could be either ot…
Is Knowledge Distillation Actually Greener? A Case Study in Machine Translation
arXiv:2602.09691v2 Announce Type: replace Abstract: Knowledge distillation (KD) is a technique to compress a larger teacher system into a smaller student. In machine translation, KD is commonly evaluated through translat…
GRRM: Group Relative Reward Modeling for Machine Translation
arXiv:2602.14028v2 Announce Type: replace Abstract: While Group Relative Policy Optimization (GRPO) offers a powerful framework for LLM post-training, its effectiveness in open-ended domains like Machine Translation hing…
A randomized global GMRES method for matrix equations
arXiv:2602.14786v2 Announce Type: replace Abstract: In this paper, we develop a new Randomized Global Generalized Minimum Residual (RGlGMRES) algorithm for efficiently computing solutions to large scale linear systems wi…
MarUco: A Markerless 6D Pose Estimation Framework for Closed-Loop Control of Surgical Continuum Manipulators
arXiv:2602.16365v2 Announce Type: replace Abstract: Flexible endoscopic continuum manipulators offer high dexterity and access to complex anatomy, but nonlinear hysteresis limits feedforward control accuracy. Closed-loop…
Ontology-Guided Neuro-Symbolic Inference: Grounding Language Models with Mathematical Domain Knowledge
arXiv:2602.17826v2 Announce Type: replace Abstract: Language models exhibit fundamental limitations -- hallucination, brittleness, and lack of formal grounding -- that are particularly problematic in high-stakes speciali…
Learning to Remember: End-to-End Training of Memory Agents for Long-Context Reasoning
arXiv:2602.18493v2 Announce Type: replace Abstract: Long-context LLMs and Retrieval-Augmented Generation defer state tracking and evidence consolidation to query time, which is brittle when facts evolve and answers depen…
Make Some Noise: Unsupervised Remote Sensing Change Detection Using Latent Space Perturbations
arXiv:2602.19881v2 Announce Type: replace Abstract: Unsupervised remote sensing change detection (UCD) aims to localise changes between two images of the same region without relying on labelled training data. Most recent…
Parallel Reference-Centric Continuous-Time Relative Localization with Augmented Clamped Non-Uniform B-Splines
arXiv:2602.22006v4 Announce Type: replace Abstract: Accurate relative localization is critical for multi-robot cooperation. In robot groups, measurements from different robots arrive asynchronously and with clock time-of…
Efficient Adaptation of ROMs for Unsteady Flows Using Data Assimilation
arXiv:2602.23188v3 Announce Type: replace Abstract: We propose an efficient retraining strategy for a parameterized Reduced Order Model (ROM) that attains accuracy comparable to full retraining while requiring only a fra…
Suffix-Constrained Greedy Search Algorithms for Causal Language Models
arXiv:2603.01243v3 Announce Type: replace Abstract: Large language models (LLMs) are powerful tools that have found applications beyond human-machine interfaces and chatbots. Beside free-form generation, there has been a…
Spatial Autoregressive Modeling of DINOv3 Embeddings for Unsupervised Anomaly Detection
arXiv:2603.02974v2 Announce Type: replace Abstract: DINO models provide rich patch-level representations that have recently enabled strong performance in unsupervised anomaly detection (UAD). Most existing methods extrac…