arXiv:2604.02627v1 Announce Type: cross Abstract: Living in a changing climate, human society now faces more frequent and severe natural disasters than ever before. As a consequence, rapid disaster response during the “Golden 72 Hours” of search and rescue becomes a vital humanitarian necessity and community concern. However, traditional disaster damage surveys routinely fail to generalize […]
Benchmarking Heritability Estimation Strategies Across 86 Configurations and Their Downstream Effect on Polygenic Risk Score Performance
arXiv:2604.02394v1 Announce Type: new Abstract: Objective: SNP heritability estimates vary substantially across estimation strategies, yet the downstream consequences for polygenic risk score (PRS) construction remain poorly characterised. We systematically benchmarked heritability estimation configurations and assessed their propagation into downstream PRS performance. Methods: We benchmarked 86 heritability-estimation configurations spanning six tool families (GEMMA, GCTA, LDAK, DPR, […]
Low-Rank Compression of Pretrained Models via Randomized Subspace Iteration
arXiv:2604.02659v1 Announce Type: cross Abstract: The massive scale of pretrained models has made efficient compression essential for practical deployment. Low-rank decomposition based on the singular value decomposition (SVD) provides a principled approach for model reduction, but its exact computation is expensive for large weight matrices. Randomized alternatives such as randomized SVD (RSVD) improve efficiency, yet […]
VeloTree: Inferring single-cell trajectories from RNA velocity fields with varifold distances
arXiv:2604.02380v1 Announce Type: new Abstract: Trajectory inference is a critical problem in single-cell transcriptomics, which aims to reconstruct the dynamic process underlying a population of cells from sequencing data. Of particular interest is the reconstruction of differentiation trees. One way of doing this is by estimating the path distance between nodes — labeled by cells […]
Trivial Vocabulary Bans Improve LLM Reasoning More Than Deep Linguistic Constraints
arXiv:2604.02699v1 Announce Type: cross Abstract: A previous study reported that E-Prime (English without the verb “to be”) selectively altered reasoning in language models, with cross-model correlations suggesting a structural signature tied to which vocabulary was removed. I designed a replication with active controls to test the proposed mechanism: cognitive restructuring through specific vocabulary-cognition mappings. The […]
Better Rigs, Not Bigger Networks: A Body Model Ablation for Gaussian Avatars
arXiv:2604.01447v2 Announce Type: replace-cross Abstract: Recent 3D Gaussian splatting methods built atop SMPL achieve remarkable visual fidelity while continually increasing the complexity of the overall training architecture. We demonstrate that much of this complexity is unnecessary: by replacing SMPL with the Momentum Human Rig (MHR), estimated via SAM-3D-Body, a minimal pipeline with no learned deformations […]
Disrupting Cognitive Passivity: Rethinking AI-Assisted Data Literacy through Cognitive Alignment
arXiv:2604.02783v1 Announce Type: cross Abstract: AI chatbots are increasingly stepping into roles as collaborators or teachers in analyzing, visualizing, and reasoning through data and domain problem. Yet, AI’s default assistant mode with its comprehensive and one-off responses may undermine opportunities for practitioners to develop literacy through their own thinking, inducing cognitive passivity. Drawing on evidence […]
Interpretable Deep Reinforcement Learning for Element-level Bridge Life-cycle Optimization
arXiv:2604.02528v1 Announce Type: new Abstract: The new Specifications for the National Bridge Inventory (SNBI), in effect from 2022, emphasize the use of element-level condition states (CS) for risk-based bridge management. Instead of a general component rating, element-level condition data use an array of relative CS quantities (i.e., CS proportions) to represent the condition of a […]
High-resolution probabilistic estimation of three-dimensional regional ocean dynamics from sparse surface observations
arXiv:2604.02850v1 Announce Type: cross Abstract: The ocean interior regulates Earth’s climate but remains sparsely observed due to limited in situ measurements, while satellite observations are restricted to the surface. We present a depth-aware generative framework for reconstructing high-resolution three-dimensional ocean states from extremely sparse surface data. Our approach employs a conditional denoising diffusion probabilistic model […]
Learning from Synthetic Data via Provenance-Based Input Gradient Guidance
arXiv:2604.02946v1 Announce Type: cross Abstract: Learning methods using synthetic data have attracted attention as an effective approach for increasing the diversity of training data while reducing collection costs, thereby improving the robustness of model discrimination. However, many existing methods improve robustness only indirectly through the diversification of training samples and do not explicitly teach the […]
Competency Questions as Executable Plans: a Controlled RAG Architecture for Cultural Heritage Storytelling
arXiv:2604.02545v1 Announce Type: new Abstract: The preservation of intangible cultural heritage is a critical challenge as collective memory fades over time. While Large Language Models (LLMs) offer a promising avenue for generating engaging narratives, their propensity for factual inaccuracies or “hallucinations” makes them unreliable for heritage applications where veracity is a central requirement. To address […]
VERTIGO: Visual Preference Optimization for Cinematic Camera Trajectory Generation
arXiv:2604.02467v1 Announce Type: cross Abstract: Cinematic camera control relies on a tight feedback loop between director and cinematographer, where camera motion and framing are continuously reviewed and refined. Recent generative camera systems can produce diverse, text-conditioned trajectories, but they lack this “director in the loop” and have no explicit supervision of whether a shot is […]