Health
1353 storiesPublic health and medicine worldwide — sourced from WHO News.
Space Generative AI with Solar Energy Harvesting
arXiv:2609.01062v1 Announce Type: new Abstract: Satellites are emerging as promising platforms to extend generative \emph{artificial intelligence} (AI) services to remote areas lacking terrestrial infrastructure. However…
Artificial Rosetta Stone: Constrained Maximum A Posteriori (MAP) Reconstruction of Symbolic Raga Sequences via Order-k Markov Models
arXiv:2609.01064v1 Announce Type: new Abstract: Reconstructing a damaged musical fragment is an inverse problem: the observed sequence contains partial information, while a raga encodes constraints limiting allowable com…
World Model-Guided Reinforcement Learning via Counterfactual User Engagement Simulation
arXiv:2609.01067v1 Announce Type: new Abstract: Reinforcement learning for user-centric agents is limited by the cost, latency, and risk of collecting online feedback, as well as by the lack of counterfactual comparisons…
OUTLETS: Output-Length Prediction from Speculative Decoding Backbones
arXiv:2609.01068v1 Announce Type: new Abstract: The heavy-tailed distribution of output lengths in Large Language Model (LLM) serving poses major challenges for resource provisioning and cluster scheduling. Although outp…
Asymptotically Optimal List Size of Random Linear Codes
arXiv:2609.01070v1 Announce Type: new Abstract: We prove that for every fixed prime power $q$, every $p\in(0,1-1/q)$, and every $\varepsilon>0$ with $1-H_q(p)-\varepsilon>0$, a random linear code over $\mathbb{F}_q$ of r…
DART: Aiming for Tail-Delay Control in Reconfigurable Networks
arXiv:2609.01071v1 Announce Type: new Abstract: Many systems serve different job classes by switching among configurations. Often, reconfiguration takes a stochastic amount of time that depends on direction and can diffe…
Let Confidence Change, Not the Prediction: Prediction-Preserving Repair for Post-hoc Calibration
arXiv:2609.01072v2 Announce Type: new Abstract: Post-hoc calibration corrects reported confidence, yet a multiclass calibrator can also change the associated top-1 prediction. Accuracy captures only the net effect of the…
Post-hoc Alignment of LLM-judges to Human Judgment Distribution
arXiv:2609.01073v1 Announce Type: new Abstract: The LLM-as-a-judge (LLMaJ) framework offers a cost-effective and reproducible solution for automatic evaluation. However, current evaluation practices typically compare LLM…
Lacan: Making Accountability in Anonymous Networks Real
arXiv:2609.01075v1 Announce Type: new Abstract: Anonymity and accountability are essential properties for our everyday activity on the Internet. However, they appear contradictory, and their reconciliation remains far fr…
JENGA: Exploiting Counter-Based RowHammer Countermeasures to Break Real-Time Predictability
arXiv:2609.01077v1 Announce Type: new Abstract: Safety-critical real-time systems must satisfy multiple dependability requirements, notably time predictability and security. In such systems, tasks must complete within bo…
StateSwap: Probing Support-Elimination Hidden States in Multiple-Choice Questions
arXiv:2609.01081v1 Announce Type: new Abstract: Large language models often answer the same multiple-choice question inconsistently when it is posed under support-oriented and elimination-oriented framings. We investigat…
Update for Decisions, Not Freshness: Goal-Oriented Status Updating and Selective Offloading at the Network Edge
arXiv:2609.01082v1 Announce Type: new Abstract: In an edge--cloud collaborative edge-computing environment, an edge node (EN) must decide whether each user task should be executed locally, forwarded to a remote service (…
Hardware Acceleration of Block-Diffusion LLM for Edge Devices
arXiv:2609.01084v1 Announce Type: new Abstract: Single-stream (batch-one) edge inference cannot amortize weight traffic across requests. Full-attention diffusion LLMs recompute the entire sequence at every step; native b…
Fine-Tuning Large Language Models to Classify Pull Request-Issue Alignments: Going Beyond Prompting
arXiv:2609.01087v1 Announce Type: new Abstract: Context: Accurate alignment between pull requests (PRs) and corresponding issues is crucial for efficient software development and maintaining code quality, as misalignment…
Adaptive Depth-Map-Guided Bundle Adjustment for Correspondence-Free Multi-View Point Cloud Registration
arXiv:2609.01089v1 Announce Type: new Abstract: Robotic processing of irregular steel scrap requires dense 3-D measurement to replace manual visual assessment in hazardous cutting workcells. The reconstructed map is used…
Modelpedia: A Catalog of Model Findings for the Meta-Science of AI
arXiv:2609.01090v1 Announce Type: new Abstract: Scientific knowledge about AI models is produced faster than the community can organize it. Every few months a new foundation model reshapes the field and hundreds of paper…
Subliminal Learning as Trait-Direction Drift: A Mechanism and Targeted Control under SFT Distillation
arXiv:2609.01091v2 Announce Type: new Abstract: Beyond intended capabilities, model distillation can transfer hidden traits from a teacher. A teacher biased by a system prompt can generate semantically clean training dat…
IT-TextFusion: Iterative Text-Image Interaction with Text-Guided Residual Refinement for Degradation-Aware Image Fusion
arXiv:2609.01092v1 Announce Type: new Abstract: Text-guided image fusion has recently emerged as an effective paradigm for integrating multi-modal information while enabling flexible and task-oriented fusion control. How…
Reliable LLM-Generated Programs for High-Energy Physics Experiments through Graph-Grounded Software Knowledge
arXiv:2609.01095v1 Announce Type: new Abstract: Extracting physics information from modern particle-physics experiments requires multistage analyses implemented on top of large and highly interconnected software ecosyste…
CRSF: Collusion-Resilient Privacy-Preserving Sensor Fusion with Byzantine-Robust Participation
arXiv:2609.01096v1 Announce Type: new Abstract: Privacy-preserving sensor fusion enables an untrusted server to compute an aggregate result over distributed sensor measurements without learning either individual inputs o…