applications

REATS: LLM Reasoning-based Ensemble Learning for Adaptive Time Series Forecasting

arXiv:2608.10149v1 Announce Type: new Abstract: Due to the diversity of real-world time series, no single forecasting model consistently dominates across all samples. Ensemble learning addresses this

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Retrieval-Augmented Vision Foundation Models for Robust Leukemia Cell Classification across Multiple Microscopy Datasets

DGX agent

arXiv:2608.10657v1 Announce Type: cross Abstract: Leukemia cell image classification is challenged by real-world domain shifts from acquisition, staining, illumination, and site protocols, causing sin

applicationsarxiv-cs-cv

12 Aug 2026

Self-Knowledge Retrieval Augmented Generation Framework for Patent Matching

arXiv:2608.11030v1 Announce Type: cross Abstract: Patent retrieval and matching based on large language models (LLMs) play a vital role in intellectual property protection. However, due to the complex

Skan AI raises $63M to give AI agents a map of enterprise work

Process intelligence company Skan AI said today it raised 63 million in a Series C round to help further develop a platform that records how enterprise work actually gets done and feeds that record to

applicationssiliconangle

The GenAI Catch-22: Use of Generative Artificial Intelligence in Norwegian Newsrooms During the 2025 Parliamentary Election

arXiv:2608.10773v1 Announce Type: cross Abstract: The increasing use of Generative Artificial Intelligence (GenAI) in journalism raises concerns about possible detrimental effects both on journalism a

When Repository Labels Are Not Image-Level Truth: A Supervision Auditing Framework for Chest Radiograph AI

arXiv:2608.10084v1 Announce Type: cross Abstract: Public chest X-ray repositories are widely used to train medical AI systems, yet their labels are typically extracted from radiology reports rather th

When Your State Estimator Has Lost The Plot: Detecting Estimator Failures Via Spectral Analysis

arXiv:2608.10623v1 Announce Type: new Abstract: Reliable onboard state estimation is essential for safe robotic operation, yet unmodeled disturbances, such as sensor aliasing or out-of-distribution no

applicationsarxiv-cs-ro

Who Gets Heeded? An Obligation-Level Audit of Responsiveness in EPA Rulemaking

arXiv:2608.10329v1 Announce Type: cross Abstract: Notice-and-comment rulemaking gives any affected party the same formal right to influence federal regulation, but formal access is not substantive cap

Accurate but Natural? Diagnosing Grammatical and Idiomatic Gaps in Japanese EFL Writing

arXiv:2608.09289v1 Announce Type: new Abstract: Second language writing research distinguishes grammatical accuracy from native-like idiomaticity, yet automated writing evaluation often conflates thes

AdaDexGrasp: Adaptive Dexterous Grasping via 3D Visuo-Tactile Representation Fusion

arXiv:2608.07600v1 Announce Type: new Abstract: Humans achieve stable and adaptive grasps by seamlessly integrating visual perception and tactile feedback, a capability that remains challenging to rep

applicationsarxiv-cs-ro

AirFlow: Context Preserving and Multi-Rate State Modeling for Air Quality Forecasting

arXiv:2608.09775v1 Announce Type: new Abstract: Accurate air quality forecasting is essential for public health and urban environmental management, but remains challenging because pollutant channels d

Analogical Learning for Cross-Scenario Generalization: Framework and Application to Intelligent Localization

arXiv:2504.08811v3 Announce Type: replace Abstract: Modern learning systems often struggle with joint learning across diverse scenarios and immediate adaptation to new ones, because they rely heavily

Backward Compatibility in Tree-Based Explanations and Enhanced CART Algorithm

arXiv:2608.08674v1 Announce Type: new Abstract: In the operation of machine learning models, model update is a fundamental process that requires careful consideration of its impact on downstream decis

Bridging the Gap Between Semantics and Reconstruction:Unifying Sign Language Translation and Production

arXiv:2608.09045v1 Announce Type: cross Abstract: Recent advances in sign language (SL) research have shown a trend toward unifying multiple sign language understanding (SLU) subtasks, such as isolate

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning

arXiv:2608.07742v1 Announce Type: new Abstract: Visual-language models (VLMs) frequently struggle with robustness issues in real-world situations due to low- or varying-quality input images. In this p

Carnot: Interpretable, Interactive, and Optimized Execution of Deep Research Queries

arXiv:2608.09532v1 Announce Type: cross Abstract: Enterprises increasingly seek to query data lakes using natural language via AI-driven tools like semantic operators or deep research agents. However,

ConMem: Contribution-Aware Memory for Long-Horizon Manufacturing Inspection Logs

arXiv:2607.28126v2 Announce Type: replace Abstract: Long-horizon steel-equipment inspection requires reasoning over heterogeneous records accumulated across repeated inspection cycles. Existing retrie

Consilience for Verifier-Free Test-Time Scaling

arXiv:2608.09898v1 Announce Type: new Abstract: Test-time scaling often uses an external verifier, such as compilers and test cases in coding or trained value functions in robotics applications, to ob

ControlRadio: Prompt-Driven Controllable Diffusion for Cross-Modal Radio Map Generation

arXiv:2608.09357v1 Announce Type: new Abstract: Radio maps describe how wireless signals propagate across space and are essential for wireless communication, sensing, and network planning. However, co

DAVE: A Decoupled Audio-Visual Enhancement Framework for Real-World Speech Separation

arXiv:2608.09288v1 Announce Type: cross Abstract: Audio-visual speech enhancement under real-world conditions remains challenging due to unreliable visual inputs and the lack of large-scale training d

Decision-Focused Learning in Network Interdiction Games

arXiv:2608.09036v1 Announce Type: cross Abstract: We study decision-focused learning (DFL) in shortest-path network interdiction (SPNI) games, a Stackelberg game where an interdictor (leader) strength

Deep probabilistic logic programming for diagnostic reasoning from incomplete information: A case study in stroke detection

arXiv:2608.08561v1 Announce Type: new Abstract: In medical applications, raw data is frequently associated with significant privacy concerns, lending particular importance to the encoding of summary s

DeepFreqMark: End-To-End Learnable Frequency-Domain Watermarking with Spherical Attack Simulation for Latent Diffusion Models

arXiv:2608.08999v1 Announce Type: cross Abstract: The proliferation of AI-generated images produced by Latent Diffusion Models (LDMs) has raised critical concerns regarding copyright infringement and

Distilling Physical Priors into Streaming World Models

arXiv:2608.07981v1 Announce Type: new Abstract: Streaming world models predict future visual states online while maintaining physically coherent dynamics over long horizons. However, their rollouts of

DoRF++: Spherical Representation Learning over Doppler Radiance Fields for Robust Wi-Fi Sensing

arXiv:2608.08381v1 Announce Type: new Abstract: Motivated by the IEEE 802.11bf effort to standardize advanced WLAN sensing, interest in Wi-Fi Channel State Information (CSI) for passive, device-free,

Dramarrator: Object-Based Audio Editing for Audio Drama Production from Books

arXiv:2608.08349v1 Announce Type: cross Abstract: Audio dramas weave dialogue, sound effects, and music into immersive stories. Creators often adapt books into audio dramas, but this process remains l

Embedding Initialization for Unseen Low-resource Languages in Multilingual NMT: A Case Study on Limbum-English Translation

arXiv:2608.07629v1 Announce Type: new Abstract: Multilingual neural machine translation models such as NLLB-200 cover 200 languages but leave thousands unsupported, including most Grassfields Bantu la

Embedding Trust: Semantic Isotropy Predicts Nonfactuality in Long-Form Text Generation

arXiv:2510.21891v2 Announce Type: replace-cross Abstract: To deploy large language models (LLMs) in high-stakes application domains that require substantively accurate responses to open-ended prompts,

EvBS: Event-guided Blur Synthesis for Domain-adaptive Motion Deblurring

arXiv:2608.08066v1 Announce Type: new Abstract: Motion deblurring has achieved remarkable progress with deep learning, yet pre-trained deblurring models often suffer from performance degradation in re

EvTrajGS: Accurate and Efficient 3D Gaussian Splatting from Unposed Event Streams

arXiv:2608.08585v1 Announce Type: new Abstract: Event cameras, with high temporal resolution, high dynamic range, and asynchronous sensing characteristics, have shown great potential for dense 3D reco

Explainable Machine Learning-Based Security and Privacy Protection Framework for Internet of Medical Things Systems

arXiv:2403.09752v4 Announce Type: replace-cross Abstract: The Internet of Medical Things transcends traditional medical boundaries, enabling a transition from reactive treatment to proactive preventio

Exploring LLM Capabilities for Situational Understanding and COLREG compliance on real-world maritime navigation scenarios

arXiv:2608.08281v1 Announce Type: new Abstract: Recently, Large Language Models (LLMs) have shown considerable capability for situational understanding, reasoning, and decision making in different dom

GeoAI-based post-segmentation quality validation of building footprints via spatial feature engineering

arXiv:2608.09048v1 Announce Type: new Abstract: Deep learning-based building footprint extraction from high-resolution imagery often produces topologically inconsistent vectors unfit for direct GIS da

Ground-Truth Neighborhood Regularization for Reinforcement Learning Post-Training of Time Series Foundation Models

arXiv:2608.08010v1 Announce Type: cross Abstract: Time series forecasting (TSF) plays an important role in a wide range of real-world applications. Recently, time series foundation models (TSFMs), pre

H2: A Dual Hybrid Semantic Data Lake Architecture for Medical Data Harmonization with Human-In-the-Loop verified, LLM Driven Metadata Annotation System

arXiv:2608.08056v1 Announce Type: new Abstract: Medical data, by its nature, exhibit a high degree of heterogeneity on multiple levels ranging from (a) different modalities like images, text and time

Hierarchical rank-evolving representation for physics-informed neural networks

arXiv:2608.09483v1 Announce Type: new Abstract: Recently, tensor-based physics-informed neural networks (T-PINNs) have received increasing attention. However, existing T-PINNs still face a fundamental

How ONESTRUCTION built the Ishigaki-IDS foundation model with AWS GenAIIC

ONESTRUCTION, with technical advisory from the AWS Generative AI Innovation Center, built Ishigaki-IDS, a foundation model specialized for construction and BIM workflows. This architectural case study

applicationsaws-ml-blog

How Simple Can It Get? From Interpretable Equations to Readable Rules for Financial Decision Making

arXiv:2608.09433v1 Announce Type: cross Abstract: In regulated domains such as finance, a model that cannot be explained cannot be deployed, yet many interpretable classifiers defeat their own purpose

Human-Guided Causal Knowledge Injection for Virtual Cells

arXiv:2608.08430v1 Announce Type: cross Abstract: Virtual cells employ machine learning models to simulate and predict cellular behaviors, serving as a critical computational framework for investigati

Hybrid Neural-Classical Correction for Frozen Time Series Foundation Models: A Comprehensive Ablation Study on High-Frequency Stock Prediction

arXiv:2608.08825v1 Announce Type: cross Abstract: Foundation models for time series forecasting demonstrate impressive zero-shot generalization but often underperform on specialized domains such as hi

Latent World Models with Monotone Planning Costs for Image-Goal Navigation

arXiv:2608.09073v1 Announce Type: new Abstract: Image-goal navigation with latent world models requires not only accurate future prediction, but also a planning cost that reliably ranks candidate acti

applicationsarxiv-cs-ro

Length-MAX Tokenizer for Language Models

arXiv:2511.20849v2 Announce Type: replace-cross Abstract: We introduce a new tokenizer for language models that minimizes the average tokens per character, thereby reducing the number of tokens needed

Leveraging the frontier ecosystem We work with neolabs like @trajectorylabs and @EngramLab and inference + post-training infra providers lik…

applicationsfireworks-ai--x

Leveraging the frontier ecosystem We work with neolabs like @trajectorylabs and @EngramLab and inference + post-training infra providers like @baseten, @FireworksAI_HQ, and @appliedcompute to post-tra

LineGraph2Road: Structural Graph Reasoning on Line Graphs for Road Network Extraction

arXiv:2602.23290v2 Announce Type: replace Abstract: Extracting routable road networks from satellite imagery requires accurate topology recovery beyond pixel-level segmentation. Recent methods decompo

Mask-aware inference with State-Space Models

arXiv:2603.04568v2 Announce Type: replace Abstract: Many real-world computer vision tasks, such as depth completion, must handle inputs with arbitrarily shaped regions of missing or invalid data. For

MeanSR: Restoration Trajectory Learning for One-Step Perceptual Super-Resolution

arXiv:2608.09405v1 Announce Type: new Abstract: Diffusion-based super-resolution (SR) achieves strong perceptual quality but requires costly iterative denoising. Existing one-step distillation methods

Metadata Reconstruction from Values Alone: Recovering Column Semantics in Undocumented Warehouses

arXiv:2608.07946v1 Announce Type: cross Abstract: Text-to-SQL benchmarks ship schemas whose column names already say what the columns mean. Production warehouses are the inverse: cryptic identifiers,

Motion-Aware Animatable Gaussian Avatars Deblurring

arXiv:2411.16758v4 Announce Type: replace Abstract: The creation of 3D human avatars from multi-view videos is a significant yet challenging task in computer vision. However, existing techniques rely