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Dastawez Jahan-Numa

World News, Faithfully Reported

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Health

988 stories

Public health and medicine worldwide — sourced from WHO News.

Dastawez Jahan-Numa

Beyond scalar losses: calibrating segmentation models via gradient vector field surgery

arXiv:2607.14338v1 Announce Type: new Abstract: Region-based loss functions, such as the Dice loss, have established themselves as the de facto standard for highly class- and region-imbalanced segmentation tasks. However…

arXiv (cs)3h ago
Dastawez Jahan-Numa

The Prover Is the Judge: Verified Security Software from AI Coding Agents in Ada/SPARK

arXiv:2607.14340v1 Announce Type: new Abstract: AI coding agents produce code faster than humans can review it. In our approach, the prover is the judge of whether the code is correct. Under a verifier-driven loop, AI ag…

arXiv (cs)3h ago
Dastawez Jahan-Numa

Beyond Visual Grasping: Benchmarking Complex Grasping from Detection to Execution

arXiv:2607.14341v1 Announce Type: new Abstract: Robust robotic grasping remains a fundamental challenge for complex real-world applications. Recent advances in large-scale models demonstrate promising capabilities for re…

arXiv (cs)3h ago
Dastawez Jahan-Numa

Value Leakage: An LLM's Answers Are Silently Shaped by Its Own Values

arXiv:2607.14345v1 Announce Type: new Abstract: People use language models for practical questions whose answers are difficult to verify. We show that models exhibit covert value leakage: the information they provide is …

arXiv (cs)3h ago
Dastawez Jahan-Numa

Learning Who to Treat When Treatment is Missing

arXiv:2607.14346v1 Announce Type: new Abstract: Policy learning methods are increasingly used to inform treatment allocation under budget constraints. Most proposed methods assume complete treatment data, yet application…

arXiv (cs)3h ago
Dastawez Jahan-Numa

HABIB_TAZ at SemEval-2026 Task 11: Disentangling Formal Logic from Content via Synthetic Training and Multi-Objective Optimization

arXiv:2607.14349v1 Announce Type: new Abstract: While Large Language Models (LLMs) excel in many general NLP tasks, their formal reasoning capabilities are often compromised by content effects, demonstrating a measurable…

arXiv (cs)3h ago
Dastawez Jahan-Numa

Dynamic Manipulation Hypergraphs for HAR: Beyond Pairwise Relations: Dynamic Manipulation Hypergraphs for Vision-Based Human Activity Recognition

arXiv:2607.14350v1 Announce Type: new Abstract: Fine-grained manipulation recognition requires modeling evolving relations among hands, objects, tools, and supporting surfaces. Conventional graph-based methods use pairwi…

arXiv (cs)3h ago
Dastawez Jahan-Numa

Capacity of Uniform Noise Channels Under Average Input Power Constraints

arXiv:2607.14352v1 Announce Type: new Abstract: The foundational work of Shannon (1948) identified the capacity of an additive noise channel under an average input power constraint as a mutual information maximization pr…

arXiv (cs)3h ago
Dastawez Jahan-Numa

Unsafe at any AUC: Unlearned Lessons from Sociotechnical Disasters for Responsible AI

arXiv:2607.14353v1 Announce Type: new Abstract: As automated decision-making and data-driven technologies pervade society and are used to manage consequential outcomes, understanding the technology's capabilities, limita…

arXiv (cs)3h ago
Dastawez Jahan-Numa

When Is Delegated Play Truthful? Within-Range Regret and the Trilemma of Aligned Delegation

arXiv:2607.14357v1 Announce Type: new Abstract: Advertisers delegate bidding to autobidders; users delegate tasks to language-model agents. A person describes what they want to an automated proxy that acts in a mechanism…

arXiv (cs)3h ago
Dastawez Jahan-Numa

Stable Voting is PSPACE-Complete

arXiv:2607.14366v1 Announce Type: new Abstract: Stable Voting and Simple Stable Voting, introduced by Holliday and Pacuit, are Condorcet-consistent voting rules defined recursively: a candidate wins if they would win aft…

arXiv (cs)3h ago
Dastawez Jahan-Numa

Dysco: Dynamic Subspace Boosting to Mitigate LoRA Interference in Federated Learning

arXiv:2607.14367v1 Announce Type: new Abstract: Federated fine-tuning of large pre-trained models increasingly relies on Low-Rank Adaptation (LoRA) to reduce communication and computation, but heterogeneous clients can m…

arXiv (cs)3h ago
Dastawez Jahan-Numa

Supervised Fine-Tuning vs. In-Context Learning: An Equilibrium Analysis of LLM Personalization under Congestion

arXiv:2607.14371v1 Announce Type: new Abstract: Large Language Models (LLMs) have revolutionized AI services, but a critical tension emerges: while personalization improves model performance, it consumes scarce computati…

arXiv (cs)3h ago
Dastawez Jahan-Numa

A Noise-Robust Elicit-to-Optimize Framework for Distortion Riskmetrics via Inverse Reinforcement Learning

arXiv:2607.14373v1 Announce Type: new Abstract: We propose a noise-robust elicit-to-optimize framework that integrates inverse reinforcement learning (IRL) and reinforcement learning (RL) for eliciting agents' risk prefe…

arXiv (cs)3h ago
Dastawez Jahan-Numa

Random Parameter Noise Does Not Make Exact ReLU Verification Easy

arXiv:2607.14375v1 Announce Type: new Abstract: We study exact verification of ReLU networks in an adversarial smoothed model. Every network weight and bias is independently perturbed by Gaussian noise, clipped to $[-2,2…

arXiv (cs)3h ago
Dastawez Jahan-Numa

MamaBench: Benchmarking LLM Robustness in Maternal and Child Health Diagnosis through Counterfactual Clinical Perturbation

arXiv:2607.14385v1 Announce Type: new Abstract: Large language models achieve strong scores on medical benchmarks, yet these benchmarks evaluate each question in isolation, providing no measure of whether a system can di…

arXiv (cs)3h ago
Dastawez Jahan-Numa

CIPHER: A Decoupled Exploration-Selection Framework for Test-Time Scaling of Data Science Agents

arXiv:2607.14386v1 Announce Type: new Abstract: Data science tasks span from closed-ended information extraction to open-ended analysis, presenting significant challenges for automation. Recent AI agents powered by langu…

arXiv (cs)3h ago
Dastawez Jahan-Numa

Chat2Scenic: An Iterative RAG-Based Framework for Scenario Generation in Autonomous Driving

arXiv:2607.14387v1 Announce Type: new Abstract: Validating autonomous driving systems requires diverse, regulation-compliant test scenarios. In simulation-based testing, scenarios are defined as executable scripts. Yet a…

arXiv (cs)3h ago
Dastawez Jahan-Numa

Why Git Is the Memory Solution for the Agentic Development Lifecycle

arXiv:2607.14390v1 Announce Type: new Abstract: Coding agents now produce a growing share of a team's code, while the reasoning behind each change -- the alternatives weighed, the constraints discovered, the approaches r…

arXiv (cs)3h ago
Dastawez Jahan-Numa

A Comparative Analysis of Machine Learning Models for Long and Short-Term Forecasting of the Egyptian Stock Market: A Focus on EGX30

arXiv:2607.14391v1 Announce Type: new Abstract: This study concentrates on predicting stock prices in the Egyptian market, focusing on the EGX30, an influential financial hub in the Middle East. While most research focus…

arXiv (cs)3h ago
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