Unlocking electronic health records: a hybrid graph RAG approach to safe clinical AI for patient QA

IntroductionElectronic health record (EHR) systems present clinicians with vast repositories of clinical information, creating a significant cognitive burden where critical details are easily overlooked. While Large Language Models (LLMs) offer transformative potential for data processing, they face significant limitations in clinical settings, particularly regarding context grounding and hallucinations. Current solutions typically isolate retrieval methods, focusing […]

BadLLM-TG: A Backdoor Defender powered by LLM Trigger Generator

arXiv:2603.15692v1 Announce Type: cross Abstract: Backdoor attacks compromise model reliability by using triggers to manipulate outputs. Trigger inversion can accurately locate these triggers via a generator and is therefore critical for backdoor defense. However, the discrete nature of text prevents existing noise-based trigger generator from being applied to nature language processing (NLP). To overcome the […]

A Framework and Prototype for a Navigable Map of Datasets in Engineering Design and Systems Engineering

arXiv:2603.15722v1 Announce Type: cross Abstract: The proliferation of data across the system lifecycle presents both a significant opportunity and a challenge for Engineering Design and Systems Engineering (EDSE). While this “digital thread” has the potential to drive innovation, the fragmented and inaccessible nature of existing datasets hinders method validation, limits reproducibility, and slows research progress. […]

Generative AI for Quantum Circuits and Quantum Code: A Technical Review and Taxonomy

arXiv:2603.16216v1 Announce Type: cross Abstract: We review thirteen generative systems and five supporting datasets for quantum circuit and quantum code generation, identified through a structured scoping review of Hugging Face, arXiv, and provenance tracing (January-February 2026). We organize the field along two axes: artifact type (Qiskit code, OpenQASM programs, circuit graphs); crossed with training regime […]

Residual Stream Duality in Modern Transformer Architectures

arXiv:2603.16039v1 Announce Type: cross Abstract: Recent work has made clear that the residual pathway is not mere optimization plumbing; it is part of the model’s representational machinery. We agree, but argue that the cleanest way to organize this design space is through a two-axis view of the Transformer. A decoder evolves information along two ordered […]

PathGLS: Evaluating Pathology Vision-Language Models without Ground Truth through Multi-Dimensional Consistency

arXiv:2603.16113v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) offer significant potential in computational pathology by enabling interpretable image analysis, automated reporting, and scalable decision support. However, their widespread clinical adoption remains limited due to the absence of reliable, automated evaluation metrics capable of identifying subtle failures such as hallucinations. To address this gap, we propose […]

VIBEPASS: Can Vibe Coders Really Pass the Vibe Check?

arXiv:2603.15921v1 Announce Type: cross Abstract: As Large Language Models shift the programming toward human-guided ”vibe coding”, agentic coding tools increasingly rely on models to self-diagnose and repair their own subtle faults — a capability central to autonomous software engineering yet never systematically evaluated. We present name, the first empirical decomposition that jointly evaluates two coupled […]

Parallelised Differentiable Straightest Geodesics for 3D Meshes

arXiv:2603.15780v1 Announce Type: cross Abstract: Machine learning has been progressively generalised to operate within non-Euclidean domains, but geometrically accurate methods for learning on surfaces are still falling behind. The lack of closed-form Riemannian operators, the non-differentiability of their discrete counterparts, and poor parallelisation capabilities have been the main obstacles to the development of the field […]

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