applications

LLM as Detector: An In-context Learning Approach for Tabular Anomaly Detection

arXiv:2608.19463v1 Announce Type: new Abstract: Anomaly detection in tabular data is challenging because abnormal samples often arise as violations of cross-feature dependencies rather than simple mar

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Multi-Modal Graph Interaction for Multi-Graph Convolution Network in Urban Spatiotemporal Forecasting

DGX agent

arXiv:1905.11395v2 Announce Type: replace Abstract: Graph convolution network based approaches have been recently used to model region-wise relationships in region-level prediction problems in urban c

applicationsarxiv-cs-lg

21 Aug 2026

OmniCamera: A Unified Framework for Multi-task Video Generation with Arbitrary Camera Control

arXiv:2604.06010v2 Announce Type: replace Abstract: Video fundamentally intertwines two crucial axes: the dynamic content of a scene and the camera motion through which it is observed. However, existi

Online Test-Time Adaptation for Generalizable Dynamic Graph Anomaly Detection

arXiv:2608.19858v1 Announce Type: new Abstract: Generalizable dynamic graph anomaly detection (DGAD) enables pretrained detectors to identify anomalies in unseen target domains without costly retraini

PO-PDDL: Learning Symbolic POMDPs from Visual Demonstrations for Robot Planning Under Uncertainty

arXiv:2606.15654v2 Announce Type: replace-cross Abstract: Real-world robot task planning must operate under both stochastic action execution and partial observability, yet constructing Partially Obser

Quantifying Event Impacts on Time Series via Multiscale Contrastive Learning

arXiv:2608.19447v1 Announce Type: new Abstract: Shocks that spread through the web, such as cybersecurity breach disclosures, can abruptly disrupt financial time series and cause substantial abnormal

Reliable Financial Named Entity Recognition under Domain Shift

arXiv:2608.19558v1 Announce Type: new Abstract: Financial AI systems often train information extractors on one textual register and deploy them across filings, news, and user-generated content, while

Rethinking Patch Based Multivariate Time Series Forecasting with Semantic Structured Partitioning

arXiv:2608.19966v1 Announce Type: new Abstract: Multivariate time series forecasting (MTSF) is a fundamental task in many real world applications. Existing patch based forecasting methods generally fa

Robust Incomplete Multimodal Sentiment Analysis via Iterative Proxy Correction

arXiv:2608.19971v1 Announce Type: new Abstract: Multimodal sentiment analysis aims to infer affective states by integrating language, visual, and acoustic cues. However, real-world multimodal inputs a

Silhouette-based Gait Foundation Model

arXiv:2512.00691v2 Announce Type: replace Abstract: Gait patterns play a critical role in human identification and healthcare analytics, yet current progress remains constrained by small, narrowly des

SynFlow: A Multidimensional Diachronic Semantic Analysis Toolkit

arXiv:2608.19472v1 Announce Type: new Abstract: Lexical semantic change (LSC) is commonly modelled through vector-space representations, but these approaches often provide limited insight into which a

Teacher-free Latent Self-distillation and Class-separable Representations for Lightweight IoT Attack Detection

arXiv:2403.15509v3 Announce Type: replace-cross Abstract: Knowledge distillation (KD) has been widely used to improve lightweight AI models by transferring soft-label knowledge from a large teacher mo

TESTNAV: Pareto-Guided Search for Compositional Robustness Testing

arXiv:2608.19882v1 Announce Type: new Abstract: Deep learning models remain vulnerable to real-world input perturbations, especially when multiple corruptions co-occur in the same input (e.g., brightn

Towards Professional Tennis Styles for Humanoid Robots with Adaptive Motion Planning and Tracking

arXiv:2608.20087v1 Announce Type: cross Abstract: Humanoid robots have recently demonstrated promising capabilities in real-world ball sports. However, achieving professional motion styles while maint

TT-net: Quantum Inspired Tensor Network Denoising in Conditional GANs

arXiv:2608.19789v1 Announce Type: new Abstract: Developed as a workhorse for classical simulations of quantum algorithms and quantum many-body systems, Tensor Network methods have entered the scientif

When Machines Speak: A Unified Generative Framework for Integrating Machine-Native Symbols into Pretrained Large Language Models

arXiv:2608.19529v1 Announce Type: cross Abstract: Many real-world AI systems represent entities, behaviors, and structured information using discrete machine-native symbols rather than natural languag

Accurate Decoding of Natural Sentences from Non-Invasive Brain Recordings

arXiv:2608.18114v1 Announce Type: cross Abstract: Restoring communication for people who have lost the ability to speak or move after a brain injury is a major challenge. While intracranial implants n

Acquisition Geometry-Assisted Whole-Group Localization of X-ray Fluorescence Maps in Optical Microscopy Images

arXiv:2608.18305v1 Announce Type: new Abstract: X-ray fluorescence (XRF) microscopy maps elemental distributions, while optical microscopy can provide complementary morphological context. Localizing X

Anthropic-backed enterprise AI venture Ode is acquiring four-year-old AI consultancy Casper for an undisclosed fee; Ode has 100+ staff after buying Fractional (Julia Hornstein/The Information)

Julia Hornstein / The Information: Anthropic-backed enterprise AI venture Ode is acquiring four-year-old AI consultancy Casper for an undisclosed fee; Ode has 100+ staff after buying Fractional — A jo

applicationstechmeme

Assessing Quality of Experience in Natural Language Generation of German Text

arXiv:2608.18888v1 Announce Type: new Abstract: The rapid advancement of Natural Language Generation (NLG) has made the reliable evaluation of generated text increasingly critical, as these systems, s

Bernstein-Vazirani Networks: Quantum Machine Learning by Interference

arXiv:2608.19043v1 Announce Type: cross Abstract: We introduce Bernstein-Vazirani Networks (BVNs), a non-variational quantum machine learning framework that leverages quantum interference for supervis

Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 1: Setting up your Snowflake environment

Healthcare, retail, and life sciences teams store large volumes of operational data in Snowflake, but turning it into predictions is hard. In Part 1 of this series, you set up your AWS account and Sno

applicationsaws-ml-blog

Candidate-Fate Accounting for Transparent Sensor Diagnostic Pipeline Search

arXiv:2608.18665v1 Announce Type: new Abstract: Industrial sensor diagnostics relies on preprocessing, representation, and classification pipelines, making automated pipeline search useful for reducin

Change Point--Aware Evaluation and Re-Calibration of PPG-Based Blood Pressure Estimation

arXiv:2608.18639v1 Announce Type: cross Abstract: Non-invasive continuous blood pressure (BP) monitoring using photoplethysmography (PPG) is a promising alternative to cuff-based measurements. However

Compiler-Guided Adaptive Proof Search with Cross-Model Synergy on Context-Dependent Theorem Proving

arXiv:2608.18084v1 Announce Type: new Abstract: Theorem proving in real-world Lean 4 projects is challenging because proofs often depend on project-specific context. While iterative refinement can use

Computer History in the Mac desktop app is now available to Pro, Business, and Enterprise users in the EEA, UK, and Switzerland.

OpenAI announced on August 13 that the **Computer History** feature of its ChatGPT desktop app will now roll out to Pro, Business and Enterprise users in the European Economic Area, United Kingdom and

applicationsopenai--x

Congrats to @harvey on Tenet, their first model and a milestone for legal AI. We’re proud to have co-developed it with them, setting the fou…

applicationsfireworks-ai--x

Congrats to @harvey on Tenet, their first model and a milestone for legal AI. We’re proud to have co-developed it with them, setting the foundation for firms to build their own specialized intelligenc

Contrasting Cost-Agnostic and Cost-Sensitive Losses under Limited Model Capacity via mathcal H-consistency

arXiv:2502.19522v2 Announce Type: replace Abstract: There is a prevalent debate in machine learning about whether practitioners should train models to optimize a task-agnostic objective (e.g., cross e

Designing Social Robots for Social-Cognition Training with Autistic Adults

arXiv:2608.18488v1 Announce Type: cross Abstract: Social robots have been widely explored as tools for autism intervention, yet this literature has focused predominantly on children and has rarely inv

applicationsarxiv-cs-ro

Discretizing Continuous Time Series for Imputation with Masked Diffusion Training

arXiv:2608.19119v1 Announce Type: cross Abstract: Time series imputation is a crucial area for reliable time series analysis, yet it remains challenging due to the complex temporal dynamics and noise

DyG^2T: Modeling Object Dynamics with 3D Gaussian Temporal-Spatial Particle Graph Transformer

arXiv:2608.18498v1 Announce Type: new Abstract: Modeling object dynamics from limited visual observations is a fundamental problem for enabling accurate motion trajectory prediction in embodied intera

Evaluating Music Context Preservation: A Multi-facet Framework for Music Editing Systems

arXiv:2512.14629v2 Announce Type: replace-cross Abstract: Music editing plays a vital role in modern music production, with applications in film, broadcasting, and game development. Recent advances in

FedCoRe: Target-Adaptive Completion for Missing Modalities in Healthcare Federated Learning

arXiv:2608.18311v1 Announce Type: cross Abstract: Federated multimodal models often assume every site has every modality, although hospitals differ in access to EHRs, chest radiographs, and ECGs. We s

From Threat Intelligence to Detection: Knowledge-driven Enrichment and Template-based Rule Grounding for Automated Sigma Rule Generation

arXiv:2608.19011v1 Announce Type: cross Abstract: Mechanisms for dynamically converting cyber threat intelligence (CTI) into actionable detection capabilities are necessary due to the rapid evolution

GraphK: Variable-Size Graph Generation with Efficient Edge Construction

arXiv:2608.18777v1 Announce Type: new Abstract: Graph generation models have advanced significantly with deep learning, yet they remain limited in scalability, flexibility, and ability to model underl

High-Flux Count-Free Single-Photon 3D Cameras

arXiv:2608.18306v1 Announce Type: new Abstract: Single-photon cameras based on single-photon avalanche diode (SPAD) technology are gaining popularity for 3D sensing, thanks to their extreme sensitivit

Image-Guided Pavement Defect Recognition in GPR Data with novel 3D Deep Learning Architecture

arXiv:2608.19177v1 Announce Type: new Abstract: Ground Penetrating Radar (GPR) is a widely adopted non-destructive sensing technology for subsurface inspection in civil and transportation engineering.

Large Language Models in Mental Health: A Systematic Review of Applications, Innovations, and Ethical Challenges

arXiv:2608.18080v1 Announce Type: new Abstract: We present a review on the applications of large language models (LLMs) in health, e.g., social media analysis, clinical conversational agents, therapy

Mapping intrinsic rank and informational gravity in complex tabular data: I developed a non-parametric, model-agnostic, information-theoretic diagnostic to bypass the limits of linear, rank, and Euclidean baselines. [R]

applicationsr-machinelearning

Links: Preprint: https://doi.org/10.5281/zenodo.22028087 Entropic Scree Function v1.0.0 / GitHub: https://github.com/tjleestjohn/Entropic-Scree TL;DR: Standard PCA fundamentally fractures non-linear d

MicroPython and CircuitPython: Pythons Quiet Takeover of IoT and Robotics

arXiv:2608.18160v1 Announce Type: cross Abstract: Background: Python has become the dominant language in software and data science, yet embedded systems have remained tied to C/C++ due to performance

Moderna/Merck just ran a 1,137-patient Phase 3 trial where every single dose was unique to that patient's tumor. It worked. The pipeline: su…

applicationsyann-lecun--x

Moderna/Merck just ran a 1,137-patient Phase 3 trial where every single dose was unique to that patient's tumor. It worked. The pipeline: surgical resection → whole exome + RNA sequencing → ML neoanti

Multi-Objective Optimization Under Uncertainty of Part Quality in Fused Filament Fabrication

arXiv:2608.18429v1 Announce Type: cross Abstract: This work presents a data-driven methodology for multi-objective optimization under uncertainty of process parameters in the fused filament fabricatio

Nice case study on using optimized functions whenever possible (except for educational purposes, though 😆)

applicationssebastian-raschka--x

Nice case study on using optimized functions whenever possible (except for educational purposes, though 😆) By switching from a hand-rolled GELU to PyTorch's built-in one, I improved my LLM training sp

On the Power of Source Screening for Learning Shared Feature Extractors

arXiv:2602.16125v3 Announce Type: replace Abstract: Learning with shared representation is widely recognized as an effective way to separate commonalities from heterogeneity across various heterogeneo

Online Conformal Anomaly Detection with Prediction-Powered Data Acquisition

arXiv:2505.01783v2 Announce Type: replace Abstract: Online anomaly detection is essential in fields such as cybersecurity, healthcare, industrial monitoring, and telecommunications, where promptly ide

Optimized Fuzzy Logic Approach with the IEEE Key Gas Method for Diagnosing Power Transformer Faults Using Dissolved Gas Analysis

arXiv:2608.18133v1 Announce Type: new Abstract: Reliable transformer fault diagnosis is essential for maintaining power system stability. The IEEE Key Gas Method (KGM), a widely utilized approach in D

Optimizing Energy Efficiency and Grid Stability via Public EV Charging Flexibility

arXiv:2608.18126v1 Announce Type: cross Abstract: This study evaluates the potential of electric vehicle (EV) charging flexibility to enhance both energy efficiency and power grid stability. Using rea

Performance Drift Detection in Machine Learning as a Service (MLaaS) for IoT Environments

arXiv:2608.18555v1 Announce Type: cross Abstract: Machine Learning as a Service (MLaaS) is a powerful cloud paradigm enabling data-driven intelligent applications in Internet of Things (IoT) environme