Search: “models”

Integrity Detection and Characterization of Malicious Injections in RAVEN II

arXiv:2609.33951v1 Announce Type: new Abstract: The increasing adoption of robotic systems in surgery, together with the expanding range of procedures they can support and the growing level of autonom

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lapanda: A Matrix-Free Differentiable Solver for Nonconvex Constrained Optimization Layers

DGX agent

arXiv:2609.33630v1 Announce Type: cross Abstract: Differentiable optimization brings the structural guarantees of mathematical optimization to network pipelines, allowing them to be trained end-to-end

safetyarxiv-cs-lg

29 Sept 2026

Latency and accuracy tradeoffs in Spiking Neural Networks

arXiv:2609.35260v1 Announce Type: new Abstract: Spiking neural networks are attractive for low-power speech command recognition, yet their latency has received far less attention than their energy eff

Learning beyond Site Bias for OOD Generalization in Brain Networks

arXiv:2605.06050v2 Announce Type: replace Abstract: Graph-based learning from functional magnetic resonance imaging (fMRI) has shown strong potential for brain network analysis. However, existing meth

safetyarxiv-cs-lg

Learning Regional Snow Water Equivalent and Snow Height Variations from Sentinel-1 InSAR Acquisitions

arXiv:2609.34614v1 Announce Type: new Abstract: Managing water resources in mountainous regions depends heavily on reliable Snow Water Equivalent (SWE) and Snow Height (HS) data, yet these variables r

Tutorials

Learning Where and What to Restore for Composite Image Restoration

arXiv:2503.17915v2 Announce Type: replace-cross Abstract: Real-world degraded images often contain multiple co-occurring degradation types, making composite image restoration fundamentally different f

tutorialsarxiv-cs-cv

LEGAU: Learning Semantic Gaussian Priors for Scalable Category-level Pose Estimation

arXiv:2609.35046v1 Announce Type: new Abstract: Category-level 6D pose estimation from a single RGB-D observation is inherently under-constrained, since partial visible geometry must be interpreted to

Length-Independent State Tracking Under a Parallel Scan

arXiv:2609.32447v1 Announce Type: new Abstract: Learning robust and scalable finite-state tracking is fundamental to sequence processing. While linear recurrent neural networks (RNNs), linear attentio

Local LMO is Secretly a Projection Method!

arXiv:2609.33383v1 Announce Type: cross Abstract: The local linear minimization oracle (Ferris and Zavriev, 1996; arXiv:2605.08850), or Local LMO, solves constrained convex problems without having to

local-aiarxiv-cs-lg

Localized time-frequency representation learning for bioacoustic classification in complex soundscapes

arXiv:2502.13440v2 Announce Type: replace-cross Abstract: Prevailing bioacoustic classifiers assign species labels to fixed time-frequency windows rather than to individual vocalizations. When multipl

LoCoVSR: Local Context Diffusion Posterior Sampling for Video Super-Resolution

arXiv:2609.32742v1 Announce Type: new Abstract: Video super-resolution (VSR) is an ill-posed inverse problem that aims to reconstruct a high-resolution (HR) video from a noisy, low-resolution (LR) ver

Logic Gate Networks and Lookup Table Networks as Lightweight Hardware Classifiers for Inter-patient ECG Arrhythmia Classification

arXiv:2609.32854v1 Announce Type: new Abstract: Deep Differentiable Logic Gate Networks (LGNs) and Lookup Table Networks (LUTNs) offer a promising approach for very low power inference due to their us

L{}ukasiewicz Neural Networks Extended: Residual Architectures and Crystallization Strategies for Interpretable Rule Extraction

arXiv:2609.33028v1 Announce Type: new Abstract: A feed-forward neural network whose weights are integers and whose activation is the truncated identity implements, neuron by neuron, the connectives of

Agents

M3OS: A Monte Carlo Graph Search-Orchestrated Multi-Agent LLM System for Evidence-Traced Molecular Optimization

arXiv:2609.34491v1 Announce Type: new Abstract: Small-molecule optimization integrates medicinal-chemistry reasoning and computational evidence through iterative, multi-objective decisions. When large

agentsarxiv-cs-lg

MaLiang-Harness: A Programmable Path to Image and Video Generation

arXiv:2609.34309v1 Announce Type: new Abstract: Executable programs offer explicit control over how images and videos are constructed, but generating runnable code is only the beginning of visual crea

Tutorials

Managing Self-Learning Experts under Per-Round Budget Constraints

arXiv:2510.22654v3 Announce Type: replace Abstract: This paper addresses the problem of sequential decision-making under learning budget constraints. Such settings naturally arise in applications like

tutorialsarxiv-cs-lg

Hardware

MarsLab: A Martian Rover Simulator for Planetary Rover Autonomous Navigation

arXiv:2609.34702v1 Announce Type: new Abstract: Future Mars missions will require rover autonomy that can operate across unstructured terrain, changing illumination, atmospheric dust, and limited comm

hardwarearxiv-cs-ro

Mask-Induced Displacement in Audio XAI via Logit Trajectory Decomposition

arXiv:2609.33486v1 Announce Type: cross Abstract: Perturbation-based XAI methods for audio classifiers often estimate feature importance by masking spectrogram regions and crediting output changes to

mmHRI: Towards Privacy-Preserving Human-Robot Interaction with Millimeter-Wave Radar

arXiv:2609.34220v1 Announce Type: cross Abstract: Assistive robots increasingly operate in many human-centered environments and perform various human-robot interaction (HRI) tasks, such as object deli

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Tutorials

Multi-Marginal Inverse Optimal Transport for Contrastive Learning Via Explicit Anchor-Positive-Negative Coupling

arXiv:2609.33741v1 Announce Type: cross Abstract: Inverse Optimal Transport (OT) based methods for representation learning learn representations such that the global OT coupling between a pair of data

tutorialsarxiv-cs-lg

Multi-Scale Semantic Mapping in Urban Environments via Observation Calibration and Policy Dependence Regularization

arXiv:2609.34833v1 Announce Type: new Abstract: Semantic mapping is fundamental to embodied navigation, yet existing methods are developed for indoor environments, where objects exhibit relatively lim

safetyarxiv-cs-cv

Muon Under Gradient Noise and the Limits of Orthogonalization Near Optima

arXiv:2609.32861v1 Announce Type: new Abstract: Muon replaces the momentum buffer of each weight matrix by its orthogonal polar factor. We ask what this orthogonalization does near an optimum, where m

Neural Dynamics as the Composition of Quantized Units

arXiv:2609.32487v1 Announce Type: new Abstract: Deep learning is commonly interpreted at two levels: the macroscopic, through aggregate trends in loss summarized by scaling laws, and the microscopic,

Neural Scaling Laws of Transformer Operator Network

arXiv:2609.33533v1 Announce Type: cross Abstract: Transformers have emerged as powerful architectures for learning solution operators of physical systems. Empirically the prediction error has been obs

Noise-adapted Neural Operator for Robust Non-Line-of-Sight Imaging

arXiv:2508.09655v3 Announce Type: replace Abstract: This work has been submitted for possible publication. Copyright may be transferred without notice, after which this version may no longer be access

One Evaluation, Any Operating Point: Hypernetwork-Amortized MeanFlow for 3D MRI Reconstruction

arXiv:2609.31655v1 Announce Type: new Abstract: Generative priors reconstruct accelerated 3D MRI well but pay heavily at deployment: tens of network evaluations per volume, and protocol-specific hyper

Agents

One Rollout Is All You Get: Fully Test-Time Adaptation for GUI Agents

arXiv:2609.34321v1 Announce Type: new Abstract: GUI agents are deployed with frozen weights and discard everything they experience on the job. Existing ways to update an agent's weights assume somethi

agentsarxiv-cs-lg

OneFixer: High-Quality and Consistent One-Step Autoregressive 3DGS Refinement for Driving Scenes

arXiv:2609.32175v1 Announce Type: new Abstract: Autoregressive video diffusion is a promising render-time fixer for 3D Gaussian Splatting (3DGS) in autonomous-driving simulation, but deployment demand

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Industry

OpenAI says users can message Dots through ChatGPT, Slack, and Microsoft Teams and join a waitlist to text via iMessage or RCS messaging on Android (Reece Rogers/Wired)

Reece Rogers / Wired: OpenAI says users can message Dots through ChatGPT, Slack, and Microsoft Teams and join a waitlist to text via iMessage or RCS messaging on Android — OpenAI's Dots are powered by

industrytechmeme

Agents

Oracle expands AI agent features with Fusion Claw

Oracle Corp. today is introducing an agentic software runtime that lets its Fusion applications carry out complex business tasks, from reconciling accounting entries to revising staffing plans when co

agentssiliconangle

Hardware

Our Secure Intelligence Institute works with researchers at Stanford, CMU, Duke, Columbia, Ohio State, and UVA. We’re also working with NVID…

Our Secure Intelligence Institute works with researchers at Stanford, CMU, Duke, Columbia, Ohio State, and UVA. We’re also working with NVIDIA and the Open Secure AI Alliance, and sharing tools and fi

hardwareperplexity--x

PACER: Progressive Availability-Conditioned Evidence Routing for Radiology Report Generation under Incomplete Clinical Context

arXiv:2609.34487v1 Announce Type: new Abstract: Radiology report generation (RRG) increasingly incorporates heterogeneous clinical evidence, such as multi-view radiographs and previous reports, whose

Phenomenon-Graph JEPA: Label-Efficient Representation Learning for Contactless Cardiorespiratory Sensing

arXiv:2609.32928v1 Announce Type: new Abstract: Millimeter-wave (mmWave) radar and RGB-D cameras can record cardiac and respiratory waveforms continuously and without contact, but labeled recordings r

PHIRL: Aligning Learned Rewards with Task Progress for Inverse Reinforcement Learning

arXiv:2609.31855v1 Announce Type: new Abstract: Human demonstrations provide dense policy-level information but sometimes lack local precision. Human feedback presents accurate local critiques, but of

local-aiarxiv-cs-ro

Physics-Informed Neural Networks for Depth-Averaged Avalanche Dynamics

arXiv:2609.34916v1 Announce Type: cross Abstract: Accurate prediction of avalanche motion is essential for hazard assessment in mountainous terrain. This study develops and evaluates a physics-informe

Policy Plasticity Matters in Offline-to-Online Reinforcement Learning: Refitting Offline Policies for Online Adaptation

arXiv:2609.33127v1 Announce Type: new Abstract: Offline-to-Online Reinforcement Learning (O2O RL) has emerged as a practical paradigm that pre-trains the policy using static offline datasets and subse

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Predicting Delayed Train Trajectories on the Dutch Railway Network: Explainable AI Evaluation of Topological, Operational and Weather Features with Tree Based Ensemble Methods

arXiv:2609.34692v1 Announce Type: new Abstract: The reliable prediction of passenger train delays is a critical component of railway management. While contemporary research frequently attempts to maxi

Predicting the Next State Is Not Enough: JEPA Representations for Lean Theorem Proving

arXiv:2609.32908v1 Announce Type: new Abstract: Neural theorem provers must both propose tactics and decide which valid successor states to explore. We study whether one-step Lean transitions provide

Prediction Limits and Koopman Closure of Geometry-Induced Soft State Abstractions

arXiv:2609.32652v1 Announce Type: cross Abstract: We study when geometry-induced soft state abstractions admit accurate finite-dimensional linear dynamics. Each state is represented by simplex-valued

Industry

President Trump signs an executive order requiring federal government agencies to refer to AI as 'Super Intelligence' or 'SI' in all official communications (Michael Shepard/Bloomberg)

Michael Shepard / Bloomberg: President Trump signs an executive order requiring federal government agencies to refer to AI as “Super Intelligence” or “SI” in all official communications — President Do

industrytechmeme

Proactive Motion Planning for Human-Robot Cooperation

arXiv:2609.32354v1 Announce Type: new Abstract: This abstract addresses the incorporation of human motion prediction into proactive and dynamic human-aware motion planning, with the goal of enabling s

researcharxiv-cs-ro

Progressive Risk Estimation for Accident Anticipation

arXiv:2609.32811v1 Announce Type: new Abstract: Accident anticipation aims to recognize anomalous driving cues before a crash while avoiding false alarms during normal driving. Existing approaches typ

Projective Normal Fields: A Convex Optimization Method for Constructing Smooth UDFs

arXiv:2609.34784v1 Announce Type: new Abstract: Constructing a smooth approximation of an unsigned distance field (UDF) from a raw point cloud is challenging because the input provides neither surface

Industry

Prompt engineering fundamentals for Amazon Quick

Prompt engineering in Amazon Quick shapes how accurately its AI-powered features respond to your requests. Part 1 of a two-part series covers the foundational principles and reusable frameworks (speci

industryaws-ml-blog

Provable Benefits of Regularization: Fast Rates for Adversarial Imitation Learning

arXiv:2609.35698v1 Announce Type: new Abstract: We study adversarial imitation learning (AIL), in which an agent learns to imitate expert demonstrations by optimizing a policy against an adversarial r

safetyarxiv-cs-lg

Quantifying How Training Gradient Sparsity Affect Spiking Neural Network Accuracy And Robustness

arXiv:2509.23762v4 Announce Type: replace-cross Abstract: Spiking Neural Networks (SNNs) have recently received increasing attention in both computational neuroscience and artificial intelligence owin

Query Expansion and Key Specialization in Transformer Attention Geometry

arXiv:2609.34273v1 Announce Type: cross Abstract: The projection of queries and keys are central to the attention mechanism in Transformer architectures. While they are mathematically symmetric, they

Reachability is not enough: Diagnosing long-range behavior in GNNs

arXiv:2609.33674v1 Announce Type: new Abstract: Graph neural networks (GNNs) are often called long-range because their architecture can connect distant nodes, but this does not show whether they use d