Search: “applications”

Three Types of Negation of Triple and its Elements and an Extension of Triple

arXiv:2609.08271v1 Announce Type: new Abstract: In various data models, the classical triple is a typical semantic data model. However, due to the design of the triple as a simple structure for repres

researcharxiv-cs-ai

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TRACE: Training Reasoning Agents for Causal Exploration with Synthesized Rewards

DGX agent

arXiv:2609.10315v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has advanced language-model reasoning in domains such as mathematics and code, where objective a

model-releasesarxiv-cs-lg

10 Sept 2026

'Transforming' LHCb: self-supervised maps of heavy-flavour decays

arXiv:2609.09275v1 Announce Type: cross Abstract: Decays of beauty and charm hadrons provide sensitive probes of physics beyond the standard model, including decays with invisible particles, in which

Unveiling Hidden Threats: Using Fractal Triggers to Boost Stealthiness of Distributed Backdoor Attacks in Federated Learning

arXiv:2511.09252v2 Announce Type: replace-cross Abstract: Traditional distributed backdoor attacks (DBA) in federated learning improve stealthiness by decomposing global triggers into sub-triggers, wh

researcharxiv-cs-ai

Agents

We've trained new models for checkbox parsing ☑️ This lets you convert checkboxes of any size and shape, filled or unfilled, into structured…

We've trained new models for checkbox parsing ☑️ This lets you convert checkboxes of any size and shape, filled or unfilled, into structured JSON that's suitable for programmatic or agentic use. Use i

agentsjerry-liu--x

A Sub-4 Approximation for Fair k-Means

arXiv:2609.07974v1 Announce Type: cross Abstract: Fairness in clustering has attracted sustained research interest, motivated by the need to ensure equitable representation of protected groups in mach

A Thermodynamic Theory of Learning Part II: History-Dependent Reachability and Continual Learning

arXiv:2602.07950v3 Announce Type: replace Abstract: We formulate plasticity as target-dependent, finite-horizon reachability under history-dependent dynamics, using standard minimum-energy control the

AI and TCAD for Inverse Design and Defect Discovery: From Simple Machine Learning to LLM

arXiv:2609.07046v1 Announce Type: new Abstract: AI has revolutionized various engineering domains, but its impact on semiconductor device design and defect discovery is still limited, due to limited d

tutorialsarxiv-cs-lg

Anti-Gravity Walking by a Flying Humanoid Robot via Thrust-Rate Input Whole-Body Model Predictive Control

arXiv:2609.07544v1 Announce Type: new Abstract: Flying humanoids are expected to perform tasks in diverse environments, while their existing locomotion is mainly limited to aerial flight and ground wa

researcharxiv-cs-ro

Assessing Covariate-Informed Grid Load Forecasting with a Time-Series Foundation Model

arXiv:2609.06656v1 Announce Type: new Abstract: Modern power systems are growing increasingly complex as they integrate diverse generation sources to meet rising demand, making accurate load forecasti

Local Ai

AstraMoE-SR: Trajectory-Guided Diffusion for Blind Satellite Jitter Deblurring and Super-Resolution

arXiv:2609.07012v1 Announce Type: cross Abstract: Pushbroom satellite imaging couples limited spatial resolution with platform attitude instability. Platform jitter produces spatially varying motion b

local-aiarxiv-cs-cv

Beyond Worst-Case Coreset Bounds for k-Clustering via Determinantal Sampling

arXiv:2609.06394v1 Announce Type: cross Abstract: Massive datasets in modern machine learning have made data reduction a central challenge, particularly for clustering tasks where memory and computati

CARDEA: Auditable Reasoning Grounded in Spatial Evidence for End-to-End Coronary Angiography Interpretation

arXiv:2609.06931v1 Announce Type: new Abstract: Invasive coronary angiography (CAG) is the gold standard for diagnosing coronary artery disease, but interpretation varies substantially among observers

safetyarxiv-cs-cv

Causal DAG Identification for Count Data via Poisson Thinning Structural Equation Models

arXiv:2609.06098v1 Announce Type: cross Abstract: Count-valued variables arise in many scientific and applied settings, yet explicit structural models that allow full identification of causal DAGs fro

Certified Topological Interaction in Neural Representations: Class Disentanglement Is Mostly Pairwise

arXiv:2609.08561v1 Announce Type: new Abstract: Class disentanglement (the separation of a representation's class-conditional point clouds along depth and over training) is usually read off descriptiv

Companion-style QA Assistance in Ego-Vision

arXiv:2609.06721v1 Announce Type: new Abstract: AI companions are envisioned as always-on assistants that support users in daily life. With this regard, we introduce BuddyVQA, a benchmark for companio

ComplicitSplat: Downstream Models are Vulnerable to Blackbox Attacks by 3D Gaussian Splat Camouflages

arXiv:2508.11854v3 Announce Type: replace Abstract: As 3D Gaussian Splatting (3DGS) gains rapid adoption in safety-critical tasks for efficient novel-view synthesis from static images, how might an ad

safetyarxiv-cs-cv

Condition aware learning enables robust prediction of oligonucleotide melting behavior across diverse chemistries and assay conditions

arXiv:2609.05454v1 Announce Type: cross Abstract: Oligonucleotide melting temperature is a fundamental determinant of nucleic acid hybridization and underpins the design of molecular diagnostics, poly

CoRe-SAM3: Conditional Semantic--Visual Reconciliation for SAM3 Crack Segmentation

arXiv:2609.05816v1 Announce Type: new Abstract: Crack segmentation requires a model to recognize target semantics while accurately recovering thin, low-contrast, and topologically continuous local str

CrACK: Adversarial Attacks on Cross-Model Consistency in Collaborative Vision Foundation Models

arXiv:2609.07499v1 Announce Type: new Abstract: Training-free collaborative pipelines that integrate Vision Foundation Models such as CLIP, SAM, and DINO achieve strong open-vocabulary dense predictio

safetyarxiv-cs-cv

Data-driven rational function neural networks: a new method for generating analytical models of rock physics

arXiv:2109.08813v1 Announce Type: cross Abstract: Seismic wave velocity of underground rock plays important role in detecting internal structure of the Earth. Rock physics models have long been the fo

DDPM Score Matching and Distribution Learning

arXiv:2504.05161v2 Announce Type: replace-cross Abstract: Score estimation is the backbone of score-based generative models (SGMs), especially denoising diffusion probabilistic models (DDPMs). A key r

Directed mixed membership stochastic blockmodel

arXiv:2101.02307v4 Announce Type: replace-cross Abstract: Mixed membership modeling for undirected networks has been extensively explored in network science over the past few years. Despite the substa

Distributed Lag Neural Additive Models

arXiv:2609.07381v1 Announce Type: cross Abstract: We introduce Distributed Lag Neural Additive Models (DLNAMs), neural-additive analogues of Distributed Lag Non-linear Models (DLNMs) for learning nonl

Distribution-free inference on the number of changepoints

arXiv:2609.08234v1 Announce Type: cross Abstract: Suppose we are given an ordered sequence of independent data whose distribution changes K times at unknown locations, for some unknown K geq 0. In thi

Do Quantum AIs Dream in Paths? Path-Integral Slow Thinking through Grover Interference

arXiv:2609.05842v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards enables large language models to think slowly, but the same training can induce policy collapse: probab

Entropy-Regularized Rank-Masked Policy Optimization for Test-Time Reinforcement Learning in Code Generation

arXiv:2609.09135v1 Announce Type: new Abstract: Existing methods for test-time reinforcement learning (TTRL) derive rewards from answer-level self-voting on unlabeled test-time tasks with canonical an

Equivariance Breaks the Learning Rate

arXiv:2609.08381v1 Announce Type: new Abstract: Equivariant networks are commonly trained with Adam, yet recent work reports that matrix-structured optimizers such as Muon can perform better on these

Event-Based De-Snowing for Autonomous Driving

arXiv:2507.20901v2 Announce Type: replace Abstract: Adverse weather conditions, particularly heavy snowfall, pose significant challenges to both human drivers and autonomous vehicles. Traditional imag

extbf{PLATO}: Preintegration Learning from Accurate Trajectory Observations for Neural Inertial Odometry

model-releasesarxiv-cs-ro

arXiv:2609.06450v1 Announce Type: new Abstract: Neural inertial odometry has demonstrated strong potential for motion estimation in challenging environments, yet inertial-only preintegration remains s

Feature Superposition in Neural Networks: From Theory to Practice

arXiv:2609.06862v1 Announce Type: new Abstract: Superposition refers to neural networks representing more features than they have dimensions. It offers a possible explanation for polysemantic neurons

FIRE3D: Feed-forward Interactive 3D Scene Reconstruction Within A Minute

arXiv:2609.08848v1 Announce Type: new Abstract: We present FIRE3D, a unified framework that takes a single RGB image or casual RGB video and transforms it into simulation-ready 3D scene assets for gam

researcharxiv-cs-cv

Formal Bayesian Transfer Learning via the Total Risk Prior

arXiv:2507.23768v2 Announce Type: replace-cross Abstract: Existing methods for transfer learning struggle to deal with situations where the source datasets are limited and not guaranteed to be well-al

Full-Page Optical Music Recognition of Handwritten Monophonic Scores

arXiv:2609.05662v1 Announce Type: new Abstract: Full-page end-to-end Optical Music Recognition seeks to transcribe entire music pages directly into symbolic notation, avoiding the limitations of tradi

researcharxiv-cs-cv

Functional Attentive Interpretable Regression

arXiv:2609.05846v1 Announce Type: cross Abstract: In function-on-function regression, the coefficient surface eta(s,t) may exhibit complex support structure---from localized patches to global patterns

tutorialsarxiv-cs-lg

Geographically Regularized AUC-Maximizing Personalized Federated Learning

arXiv:2609.08379v1 Announce Type: new Abstract: Accurate diagnostic and risk-prediction models are important for supporting clinical decision-making during infectious disease outbreaks. However, priva

tutorialsarxiv-cs-lg

GeoHeight-Bench: Towards Height-Aware Multimodal Reasoning in Remote Sensing

arXiv:2603.25565v2 Announce Type: replace Abstract: Current Large Multimodal Models (LMMs) in Earth observation are predominantly evaluated on planar optical tasks and often neglect the vertical dimen

Google is a Leader in the 2026 Gartner® Magic Quadrant™ for Enterprise AI Assistants

model-releasesgoogle-cloud-ai

We are excited to share that Gartner has named Google a Leader in its inaugural 2026 Magic Quadrant for Enterprise AI Assistants. In this comprehensive evaluation of top enterprise AI assistant vendor

Hardware

GPU-Enabled Large-Scale Optimization Using Randomized Linear Algebra

arXiv:2609.08136v1 Announce Type: new Abstract: This paper introduces rlaopt, a PyTorch-based package for large-scale optimization and scientific computing using randomized numerical linear algebra (R

hardwarearxiv-cs-lg

HB-PVI: A Hierarchical Bayesian Personalization and Value-of-Information Framework for Complex Activity Recognition

arXiv:2609.05582v1 Announce Type: new Abstract: Personalization can improve activity-recognition performance, but participant-specific gains are heterogeneous, and every additional calibration label h

HGGT: Robust and Flexible 3D Hand Mesh Reconstruction from Uncalibrated Images

arXiv:2603.23997v3 Announce Type: replace Abstract: Recovering high-fidelity 3D hand geometry from images is a critical task in computer vision, holding significant value for domains such as robotics,

tutorialsarxiv-cs-cv

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments?

arXiv:2412.09529v4 Announce Type: replace Abstract: Radiology, with its heterogeneous modalities, anatomies, and evolving protocols, is a natural yet high-stakes testbed for agentic AI. As LLMs grow m

Human-Centric Image Captioning with Subject-Centered Spatial Understanding

arXiv:2609.08300v1 Announce Type: new Abstract: While multimodal large language models (MLLMs) achieve remarkable performance on generic image captioning, they frequently suffer from structural halluc

Interpretable and Fair Generalized Additive Neural Networks via Multi-objective Learning

arXiv:2609.05946v1 Announce Type: new Abstract: Interpretability and fairness are two of the most emphasized dimensions in trustworthy artificial intelligence (AI). Various explainable AI methods have

Interpretable Network-assisted Random Forest+

arXiv:2509.15611v2 Announce Type: replace-cross Abstract: Machine learning algorithms often assume that training samples are independent. When data points are connected by a network, the induced depen

Introducing HALC: A general pipeline for the systematic and reliable construction of prompts for automated coding with LLMs in the computational social sciences

arXiv:2507.21831v2 Announce Type: replace-cross Abstract: LLMs are seeing widespread use for task automation, including automated coding in the social sciences. However, even though researchers have p

Is Single-View Mesh Reconstruction Ready for Robotics?

arXiv:2505.17966v3 Announce Type: replace-cross Abstract: This paper evaluates single-view mesh reconstruction models for their potential in enabling instant digital twin creation for real-time planni

researcharxiv-cs-cv

Iterative Audio Separation with Mixture Consistency via MIMO Model Extension

arXiv:2609.07226v1 Announce Type: cross Abstract: This paper proposes a general framework for stable and effective iterative audio separation with mixture consistency by extending source separation mo