The paper proposes FI-LDP-HGAT, a novel framework that combines a hierarchical graph attention network with feature-importance-aware anisotropic differential privacy to enable high-utility, privacy-pr…

The paper introduces SAMSEM, a generalized and scalable model based on SAM2, which significantly improves metal line segmentation across diverse and unseen integrated circuit (IC) samples.

The paper proposes a visual program synthesis framework using a VLM to generate accurate training data for semiconductor inspection, mitigating the sim-to-real gap by applying input binarization to st…

The paper introduces OmniMatBench, a comprehensive, human-calibrated multimodal reasoning benchmark covering 19 materials science subfields, revealing that current multimodal language models (MLLMs) h…

The paper proposes an end-to-end, deployable blueprint for an in-line machine-vision system that not only inspects carpet defects in real-time but also systematically collects and labels defect data t…

This paper presents a unified framework for end-to-end co-design of neural network processors.

IstGPT introduces a novel LLM-based framework for real-time, fine-grained anomaly detection in complex industrial cyber-physical systems, achieving state-of-the-art performance across multiple benchma…

The paper introduces ProvMind, a provenance-grounded reasoning framework that significantly improves materials synthesis process optimization by accurately predicting optimal synthesis routes under ch…

This review surveys advanced techniques—including generative models, multimodal learning, and closed-loop workflows—for automated inverse materials design, enabling the targeted discovery of novel cry…

The paper proposes a novel multimodal learning approach to predict the properties of new bilayer 2D materials formed by stacking dissimilar functional layers.

VEDAL introduces a variational, error-driven asynchronous learning framework to efficiently prune 3D Gaussian Splatting, achieving high compression ratios with minimal loss in novel view synthesis qua…

The paper reframes industrial visual sim-to-real transfer as a domain-gap problem categorized by the availability of explicit object geometry (CAD), arguing that the required prior evidence dictates t…

The paper proposes using a mask-conditioned latent diffusion model to generate synthetic, labeled TEM images for data augmentation, achieving small but measurable performance improvements in defect de…

The paper introduces a physics-informed active learning framework to optimize GaN tri-gate FinFETs for vertical power delivery, identifying a multi-fin device (D1) that significantly outperforms a sin…

The paper proposes a Ferroelectric Charge-Domain Compute Cell (FCDC) using HZO memcapacitors to perform attention computation, achieving significant energy efficiency gains, especially for long-reside…

The paper introduces a structured benchmark (TGAD) showing that current text-guided anomaly detection models often overstate their language conditioning, as performance significantly degrades when the…

GaMi is a multimodal material identification system that uses mmWave and acoustic sensing with a cross-modal subtractive disentanglement framework to achieve high accuracy (95.2%) for material identif…

The paper introduces a method using a U-Net CNN to acquire and estimate detailed sub-surface scattering properties by learning the pixel footprint response, enabling high-resolution relighting of obje…

The paper proposes a comprehensive monitoring and triage methodology for agentic systems, demonstrating that structural defects mask task-level errors and require specialized monitoring scopes for det…