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988 storiesPublic health and medicine worldwide — sourced from WHO News.
Intelligent Three Level Learning Architecture for Autonomous UAV Swarms in Search and Rescue
arXiv:2607.14093v1 Announce Type: new Abstract: This paper presents a novel three level hierarchical learning architecture for autonomous UAV swarms performing search and rescue operations. Unlike conventional approaches…
HG-RAG: Hierarchy-Guided Retrieval-Augmented Generation for Structured Knowledge Graphs
arXiv:2607.14095v1 Announce Type: new Abstract: Retrieval Augmented Generation (RAG) has proven to be a widely successful process at improving the quality of outputs from a Large Language Model (LLM) for wider context. H…
IMEX Interaction-Based Model Explanation
arXiv:2607.14096v1 Announce Type: new Abstract: In predictive modeling, the ability to explain why a model produces a given target prediction has become increasingly important [5, 10]. Black-box models do not provide a t…
RegNetAgents: A Multi-Agent Framework for Cross-Network Regulatory Driver Identification in Cancer Genomics
arXiv:2607.14097v1 Announce Type: new Abstract: We introduce RegNetAgents, an AI-oriented multi-agent framework for structured, query-driven regulatory candidate identification across heterogeneous gene regulatory networ…
Just Keep Prompting: Evaluating Repetitive Socratic Prompting in VLMs
arXiv:2607.14099v1 Announce Type: new Abstract: Deploying Vision-Language Models (VLMs) in real-world settings requires not only strong visual reasoning but also stability under sustained conversational pressure. We intr…
Quantum Compositional NLP for Arabic: Grammar, Morphology, and Word Sense in Circuit Topology
arXiv:2607.14100v1 Announce Type: new Abstract: We present the first application of pregroup grammar-based quantum compositional natural language processing (QNLP) to Arabic; a morphologically rich, free-word-order langu…
LBA: Textual Hard-Label Adversarial Attack under Low Query Budgets
arXiv:2607.14101v1 Announce Type: new Abstract: Generating high-quality adversarial texts with low query budgets remains a challenging problem in the hard-label scenario. Most existing approaches rely on greedy algorithm…
UniSAGE: Unifying Static and Dynamic Attributes with Hyper-Structure
arXiv:2607.14102v1 Announce Type: new Abstract: With the rapid growth of digital data, real-world applications increasingly involve hierarchical information that combines static attributes with dynamic records. Modeling …
Latent Communication Between Language Model Agents: Channels, Alignment, and the Limits of Text
arXiv:2607.14103v1 Announce Type: new Abstract: Multi-agent systems (MAS) are utilized in many contexts and many professions. Those MAS rely on inter-agent communication, usually implemented by clear-text message passing…
UzWordnet and Generative AI for Learning Uzbek by Game Playing
arXiv:2607.14104v1 Announce Type: new Abstract: This paper presents an educational system architecture that enables learners to practice the Uzbek language through game-playing. The architecture integrates UzWordnet and …
Automatically Evolving Prompt Guidelines for Task-Specific Optimization
arXiv:2607.14105v1 Announce Type: new Abstract: For Large Language Models to reliably answer user queries, users must clearly specify requirements, context, and constraints. In practice, however, user queries are often u…
Token Time Continuous Diffusion for Language Modeling
arXiv:2607.14106v1 Announce Type: new Abstract: In this paper we introduce token time continuous diffusion (TTCD), a new diffusion language model which (a) operates in continuous space, deterministically mapping Gaussian…
Polestar: Drift-Aware Cache Calibration and Token Commitment for Efficient Inference of Diffusion LLMs
arXiv:2607.14107v1 Announce Type: new Abstract: The inference efficiency of diffusion large language models (dLLMs) is constrained by two challenges: bidirectional attention precludes efficient KV-cache reuse, while incr…
Eta Given Delta: Defining LLM Tool Efficiency With Marginal Tool Utility
arXiv:2607.14108v1 Announce Type: new Abstract: This paper introduces tool efficiency, a new quantitative metric to evaluate the rate of useful tool calls in an LLM agent trajectory. To ensure that tool efficiency is wel…
Simplicity Paradox: Debunking myths about prompting and datasets for LLM evaluation
arXiv:2607.14109v1 Announce Type: new Abstract: Probing the capabilities of Large Language Models (LLMs) and building robust solutions for Multiple-Choice Question Answering (MCQA) remain central challenges in natural la…
MAPS: Modeling Co-Existing Subjective Perspectives and Shared Meaning in Multi-Agent Cognitive Dialogue
arXiv:2607.14110v1 Announce Type: new Abstract: Human dialogue involves more than exchanging information; it also expresses beliefs, emotions, and subjective cognitive styles. Yet current AI dialogue systems often enforc…
Introspection Fine-Tuning (IFT): Training Small LLMs to Introspect
arXiv:2607.14111v1 Announce Type: new Abstract: Can small language models detect and report on perturbations their own internal activations? We investigate this question through the lens of activation steering: injecting…
Information-Theoretic Limits of Reliability and Scaling in Language Models
arXiv:2607.14112v1 Announce Type: new Abstract: Large language models (LLMs) are evaluated as though perfect reliability is achievable for any task given sufficient scale. We show this assumption is information-theoretic…
T5-CSBoost: Adversarial Perturbation Resistant LLM Fingerprinting
arXiv:2607.14113v1 Announce Type: new Abstract: While many AI-generated text (AIGT) detectors achieve strong performance on clean inputs, their accuracy degrades significantly under light paraphrasing, word substitutions…
CoEvoT: Co-Evolving Chain-of-Thought Prompting for Graph-LLM Reasoning
arXiv:2607.14114v1 Announce Type: new Abstract: Graph learning under distribution shift presents a persistent challenge, where models adapt to new graphs with limited or even no supervision. Recent graph--LLM approaches …