PRECURSOR25 Sep, 09:46
arXiv:2609.29672v1 Announce Type: new Abstract: Artificial intelligence helps education most where an essential provision has been rationed by cost. For language learners that provision is a teacher's voice, which binds listening, reading, speaking, and writing into one act. Published evidence shows why most learners lack…
capabilitydeploymentconstraintspolicy
preprint; not peer reviewed
PRECURSOR24 Sep, 09:16
BackgroundLarge language models (LLMs) can support systematic reviews, but accurate individual outputs do not establish whether the final synthesis preserves the clinical question, accounts for statistical dependence and incorporates corrections. ObjectiveTo develop and evaluate a framework linking LLM-assisted evidence…
capabilitydeploymentconstraints
medRxiv preprint; not peer reviewed and not clinical advice
PRECURSOR24 Sep, 09:16
BackgroundUnstructured free-text narratives in electronic health records (EHRs) contain critical clinical information that is not captured by structured standard codes. In Catalonia, primary care notes follow a semi-structured format known as MEAP (in Catalan). However, extracting structured variables using cloud-hosted…
capabilitydeploymentconstraints
medRxiv preprint; not peer reviewed and not clinical advice
PRECURSOR25 Sep, 09:46
arXiv:2609.28684v1 Announce Type: new Abstract: Encoding input coordinates with sinusoidal functions into multi-layer perceptrons (MLPs) has proven effective for implicit neural representations (INRs) of surfaces defined as zero-level sets. However, existing methods often struggle to balance training efficiency, rendering…
capabilitydeploymentconstraints
preprint; not peer reviewed
PRECURSOR25 Sep, 09:46
arXiv:2609.28757v1 Announce Type: new Abstract: An estimated 1 billion people worldwide live with vision impairment, yet current vision-language models (VLMs) produce descriptions too vague for safe navigation by blind and low-vision (BLV) users. Large VLMs can generate high-quality audio-description-compliant narrations but…
capabilitydeploymentpolicy
preprint; not peer reviewed
PRECURSOR25 Sep, 09:46
arXiv:2609.28956v1 Announce Type: new Abstract: Recent advances in video object segmentation with Multimodal Large Language Model (MLLM) reasoning have demonstrated the effectiveness of using a single textual token, such as SEG, to predict segmentation masks across images and videos. However, we observe that this…
capabilitydeploymentconstraints
preprint; not peer reviewed
PRECURSOR25 Sep, 09:46
arXiv:2609.29029v1 Announce Type: new Abstract: Onboard vision-language models could enable satellites to answer queries directly, but exhaustive tiled inference over high-resolution imagery is slow and energy-intensive. We identify answer-invariant token redundancy (AITR): image tiles and vision tokens that can be removed…
capabilitydeploymentconstraints
preprint; not peer reviewed
PRECURSOR25 Sep, 09:46
arXiv:2609.29240v1 Announce Type: new Abstract: Text image super-resolution (TSR) aims to recover visually faithful and readable text under unknown degradations. Existing diffusion-based methods typically rely on multi-step prediction of either the high-resolution image or its text prior, resulting in prohibitive…
capabilitydeploymentconstraints
preprint; not peer reviewed
PRECURSOR25 Sep, 09:46
arXiv:2609.29334v1 Announce Type: new Abstract: Image denoising remains a fundamental problem in image restoration, with applications in photography, biomedical, and scientific imaging. Modern deep neural networks achieve strong performance by learning powerful image priors, but often rely on large black-box models with…
capabilitydeploymentconstraints
preprint; not peer reviewed
PRECURSOR25 Sep, 09:46
arXiv:2609.29347v1 Announce Type: new Abstract: Event cameras provide a high dynamic range and preserve brightness-change cues in lighting conditions where conventional RGB frames may be noisy or saturated. To benchmark event-guided restoration across a broad illumination range, we organized the SEE Challenge 2026 with the…
capabilitydeploymentconstraints
preprint; not peer reviewed
PRECURSOR25 Sep, 09:46
arXiv:2609.29457v1 Announce Type: new Abstract: Industrial anomaly detection (IAD) is evolving beyond conventional detection and localization toward multimodal inspection systems that can describe, explain, and reason about fine-grained defects. Although recent multimodal large language model (MLLM)-based methods improve…
capabilitydeploymentconstraints
preprint; not peer reviewed
PRECURSOR25 Sep, 09:46
arXiv:2609.29581v1 Announce Type: new Abstract: Although diffusion-based methods have substantially improved the controllability of multimodal face synthesis, their semantic alignment remains suboptimal because most existing approaches rely on implicit latent-space objectives to model the relationship between denoising…
capabilitydeploymentconstraints
preprint; not peer reviewed