arXiv:2601.22264v2 Announce Type: replace-cross Abstract: In principle, Continuous Integration (CI) pipeline failures provide valuable feedback to developers on code-related errors. In practice, however, pipeline jobs often fail intermittently due to non-deterministic tests, network outages, infrastructure failures, resource exhaustion, and other reliability issues. These intermittent (flaky) job failures lead to substantial inefficiencies: wasted computational resources from […]
The Geometric Alignment Tax: Tokenization vs. Continuous Geometry in Scientific Foundation Models
arXiv:2604.04155v1 Announce Type: cross Abstract: Foundation models for biology and physics optimize predictive accuracy, but their internal representations systematically fail to preserve the continuous geometry of the systems they model. We identify the root cause: the Geometric Alignment Tax, an intrinsic cost of forcing continuous manifolds through discrete categorical bottlenecks. Controlled ablations on synthetic dynamical […]
Evaluating Artificial Intelligence Through a Christian Understanding of Human Flourishing
arXiv:2604.03356v1 Announce Type: new Abstract: Artificial intelligence (AI) alignment is fundamentally a formation problem, not only a safety problem. As Large Language Models (LLMs) increasingly mediate moral deliberation and spiritual inquiry, they do more than provide information; they function as instruments of digital catechesis, actively shaping and ordering human understanding, decision-making, and moral reflection. To […]
VERT: Reliable LLM Judges for Radiology Report Evaluation
arXiv:2604.03376v1 Announce Type: new Abstract: Current literature on radiology report evaluation has focused primarily on designing LLM-based metrics and fine-tuning small models for chest X-rays. However, it remains unclear whether these approaches are robust when applied to reports from other modalities and anatomies. Which model and prompt configurations are best suited to serve as LLM […]
Toward Full Autonomous Laboratory Instrumentation Control with Large Language Models
arXiv:2604.03286v1 Announce Type: new Abstract: The control of complex laboratory instrumentation often requires significant programming expertise, creating a barrier for researchers lacking computational skills. This work explores the potential of large language models (LLMs), such as ChatGPT, and LLM-based artificial intelligence (AI) agents to enable efficient programming and automation of scientific equipment. Through a case […]
Position: Science of AI Evaluation Requires Item-level Benchmark Data
arXiv:2604.03244v1 Announce Type: new Abstract: AI evaluations have become the primary evidence for deploying generative AI systems across high-stakes domains. However, current evaluation paradigms often exhibit systemic validity failures. These issues, ranging from unjustified design choices to misaligned metrics, remain intractable without a principled framework for gathering validity evidence and conducting granular diagnostic analysis. In […]
GENFIG1: Visual Summaries of Scholarly Work as a Challenge for Vision-Language Models
arXiv:2604.04172v1 Announce Type: cross Abstract: In many science papers, “Figure 1” serves as the primary visual summary of the core research idea. These figures are visually simple yet conceptually rich, often requiring significant effort and iteration by human authors to get right, highlighting the difficulty of science visual communication. With this intuition, we introduce GENFIG1, […]
TIGFlow-GRPO: Trajectory Forecasting via Interaction-Aware Flow Matching and Reward-Guided Optimization
arXiv:2603.24936v2 Announce Type: replace-cross Abstract: Human trajectory forecasting is important for intelligent multimedia systems operating in visually complex environments, such as autonomous driving and crowd surveillance. Although Conditional Flow Matching (CFM) has shown strong ability in modeling trajectory distributions from spatio-temporal observations, existing approaches still focus primarily on supervised fitting, which may leave social norms […]
A reconfigurable smart camera implementation for jet flames characterization based on an optimized segmentation model
arXiv:2604.03267v1 Announce Type: cross Abstract: In this work we present a novel framework for fire safety management in industrial settings through the implementation of a smart camera platform for jet flames characterization. The approach seeks to alleviate the lack of real-time solutions for industrial early fire segmentation and characterization. As a case study, we demonstrate […]
3D-IDE: 3D Implicit Depth Emergent
arXiv:2604.03296v1 Announce Type: cross Abstract: Leveraging 3D information within Multimodal Large Language Models (MLLMs) has recently shown significant advantages for indoor scene understanding. However, existing methods, including those using explicit ground-truth 3D positional encoding and those grafting external 3D foundation models for implicit geometry, struggle with the trade-off in 2D-3D representation fusion, leading to suboptimal […]
IPSL-AID: Generative Diffusion Models for Climate Downscaling from Global to Regional Scales
arXiv:2604.03275v1 Announce Type: cross Abstract: Effective adaptation and mitigation strategies for climate change require high-resolution projections to inform strategic decision-making. Conventional global climate models, which typically operate at resolutions of 150 to 200 kilometers, lack the capacity to represent essential regional processes. IPSL-AID is a global to regional downscaling tool based on a denoising diffusion […]
Incomplete Multi-View Multi-Label Classification via Shared Codebook and Fused-Teacher Self-Distillation
arXiv:2604.04170v1 Announce Type: cross Abstract: Although multi-view multi-label learning has been extensively studied, research on the dual-missing scenario, where both views and labels are incomplete, remains largely unexplored. Existing methods mainly rely on contrastive learning or information bottleneck theory to learn consistent representations under missing-view conditions, but loss-based alignment without explicit structural constraints limits the […]