Search: “models”

Decentralized Safe Multi-Agent Reinforcement Learning via Predictive Shielding

arXiv:2609.07618v1 Announce Type: cross Abstract: Environments are increasingly populated by multiple robots performing independent tasks with limited prior knowledge of each other. Deploying such mul

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Decision-Aware Suffix Prediction and Reasoning of Business Processes

DGX agent

arXiv:2609.06169v1 Announce Type: new Abstract: Suffix prediction forecasts the remaining sequence of events of a running case until completion. Most approaches rely on neural networks trained on even

researcharxiv-cs-lg

9 Sept 2026

Decision-Centered Abstractions via Orthogonal Estimation of Difference-of-Q Functions

arXiv:2406.08697v4 Announce Type: replace-cross Abstract: Offline reinforcement learning enables evaluation and optimization of sequential decisions from historical data, when it is not possible to de

Decoder-Side Semantic Conditioning for Low-Bitrate Neural Speech Compression

arXiv:2512.21653v2 Announce Type: replace-cross Abstract: Speech codecs are usually optimized for waveform fidelity, allocating bits to acoustic detail that can be inferred from linguistic structure.

Tutorials

Decomposing LLM-Judge Uncertainty to Target Expert Labels

arXiv:2609.06444v1 Announce Type: cross Abstract: An LLM judge evaluates outputs at scale. Experts should label only where it is least sure. Its natural escalation signal conflates two uncertainties:

tutorialsarxiv-cs-lg

Deep Learning Approach to Bearing and Induction Motor Fault Diagnosis via Data Fusion

arXiv:2506.11032v2 Announce Type: replace Abstract: Convolutional Neural Networks (CNNs) are used to evaluate accelerometer and microphone data for bearing and induction motor diagnosis. A Long Short-

Deep Learning for Biopsy-Free Subtyping of Basal Cell Carcinoma from Dermatoscopic Images

arXiv:2609.07180v1 Announce Type: new Abstract: Basal Cell Carcinoma (BCC) is the most common type of skin cancer, accounting for nearly 80% of skin cancer di- agnoses. Its optimal clinical management

Depth-to-Image Synthesis-Driven Generative Unguided Depth Completion

arXiv:2609.06007v1 Announce Type: new Abstract: Guided depth completion methods heavily depend on RGB quality and alignment, while unguided ones often suffer from limited precision due to the absence

safetyarxiv-cs-cv

Distillation as Probability Transport: Routed On-Policy Distillation

arXiv:2609.08337v1 Announce Type: new Abstract: On-policy distillation (OPD) transfers teacher knowledge on student-generated trajectories, but efficient sampled objectives reduce the teacher distribu

Distributed Secure Learning Control for Large-scale Multirobots under Stealthy Actuator Attacks

arXiv:2609.06896v1 Announce Type: new Abstract: Distributed learning control for multirobot systems (MRS) offers significant flexibility in presence of uncertainties but lacks provable performance gua

ECHO: Dyadic 3D Facial Motion Generation with Asymmetric Deterministic Articulation and Stochastic Reaction

arXiv:2609.05506v1 Announce Type: cross Abstract: We propose ECHO for dyadic 3D facial motion generation under a strict dual-stream audio-only setting, formulating the problem as an asymmetric task in

EdMCGS: Event-Driven Markov Chain Gaussian Splatting for Extreme-Low-Frame-Rate Dynamic Scene Reconstruction

arXiv:2609.08332v1 Announce Type: new Abstract: We present EdMCGS (Event-driven Markov chain Gaussian Splatting), an end-to-end method for reconstructing dynamic 3D scenes from extreme-low-frame-rate

applicationsarxiv-cs-cv

Efficient and Microphone-Fault-Tolerant 3D Sound Source Localization

arXiv:2505.20961v2 Announce Type: replace-cross Abstract: Sound source localization (SSL) is a critical technology for determining the position of sound sources in complex environments. However, exist

local-aiarxiv-cs-lg

Agents

Efficient Exploration Is Enough

arXiv:2609.07575v1 Announce Type: new Abstract: This work introduces an alternative view of efficient exploration and studies its theoretical and empirical implications in the absence of extrinsic rew

agentsarxiv-cs-lg

EgoNeMo: Transferable Map of Pedestrian Dynamics via Egocentric LiDAR Scan

arXiv:2609.06195v1 Announce Type: new Abstract: This paper proposes a transferable Map of Dynamics (MoD) framework that generalizes to unknown environments using only egocentric 3D LiDAR point clouds

Endogenous Exploration in Reinforcement Learning with Intrinsic Curiosity

arXiv:2609.05650v1 Announce Type: new Abstract: We propose a reinforcement learning framework in which exploration is driven by intrinsic curiosity, designed for scenarios where environments are non-s

Hardware

FALCON-S: Fixed-wing ground-effect Aerodynamics Simulator and Flight Control Learning Suite

arXiv:2609.06046v1 Announce Type: cross Abstract: We present a modular, high-fidelity simulation framework for the development and benchmarking of flight control strategies in fixed-wing aerial robots

hardwarearxiv-cs-lg

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

Fixed-Dimensional Latent Flow for Generating Variable-Size 3D Molecules

arXiv:2609.08333v1 Announce Type: cross Abstract: In molecular discovery, molecule size is coupled to composition, structure, and other target properties. Yet most 3D generators require molecule size

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

From Explicit References to Scene Manifolds: Distributional Fidelity and Realism for Radiance Field Quality Assessment

arXiv:2609.07346v1 Announce Type: new Abstract: Radiance field representations such as 3D Gaussian Splatting (3DGS) enable high-quality novel view synthesis but can introduce complex, view-dependent a

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

Graph-Based Safe Reinforcement Learning for Multi-Agent Systems with Time-Varying Topology

arXiv:2609.08802v1 Announce Type: new Abstract: This paper presents a graph-based safe multi-agent reinforcement learning (MARL) framework for cooperative navigation with time-varying topology. To add

Guiding Worker Self-Selection in Crowdsourcing Contests: An LLM-Augmented Algorithmic Approach

arXiv:2609.07749v1 Announce Type: new Abstract: Crowdsourcing platforms coordinate large pools of online workers who strategically choose which contests to enter and how much effort to invest. This se

Heat Field Signatures: From Point Clouds to Smooth Geometry

arXiv:2609.07975v1 Announce Type: new Abstract: Bringing multiscale geometric analysis directly to irregular point clouds remains difficult: quantities such as local dimension, anisotropy, density var

applicationsarxiv-cs-lg

Tutorials

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

HOPE: Heterophily-Aware Open-Set Node Classification with Pseudo-Extrapolation

arXiv:2609.08685v1 Announce Type: new Abstract: Standard open-set node classification methods rely on the homophily assumption, where connected nodes share labels. However, real-world graphs are often

applicationsarxiv-cs-lg

Hypersolid: Emergent Vision Representations via Short-Range Repulsion

arXiv:2601.21255v2 Announce Type: replace Abstract: A central problem in self-supervised learning is preventing representation collapse. Most methods avoid it through global mechanisms, such as contra

safetyarxiv-cs-cv

IM-ENGINE: Image Editing for Embodied Data Generation

arXiv:2609.06279v1 Announce Type: cross Abstract: Learning-based manipulation requires supervision that is both semantically meaningful and physically executable, but current data pipelines often prov

Information-Guided Safe Reinforcement Learning for Autonomous Gas Source Localization using sUAS

arXiv:2609.05569v1 Announce Type: new Abstract: The autonomous localization of fugitive gas emissions using small Unmanned Aircraft Systems (sUAS) constitutes a fundamentally ill-posed inverse problem

local-aiarxiv-cs-ro

Infrastructure-based Monocular 3D Vehicle Localization Framework with Experimental Validation

arXiv:2609.05523v1 Announce Type: new Abstract: This paper presents a one-stage learning framework that maps monocular roadside-camera images directly to vehicle states in a ground-fixed coordinate fr

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

Introductory Notes on Learning^2

arXiv:2609.06546v1 Announce Type: cross Abstract: Although machine learning can be used to predict the evolution of physical systems from data, a formulation that learns only the system state at each

KBBQ: A Predictive Noise Law and the Limits of Spectrum Flattening in FP4 Quantization

arXiv:2609.08135v1 Announce Type: new Abstract: We develop a second-order theory of quantization noise in matrix multiplication in which the quantization format is characterized by the variance it ass

Knowledge-Guided Hierarchical Policy Learning for High-Precision Cylindrical Assembly under Tight Tolerances

arXiv:2609.06522v1 Announce Type: new Abstract: A hybrid hierarchical learning framework is proposed to achieve high-precision assembly of 170mm cylindrical components with tolerance of 0.1mm. The low

LASSNet: Level-Aware Availability-Conditioned Spatial-Semantic Fusion for Brain Tumor Segmentation with Missing MRI Modalities

arXiv:2609.06733v1 Announce Type: new Abstract: Brain tumor segmentation from multimodal MRI relies on complementary evidence across four imaging sequences, yet one or more modalities may be unavailab

Latent-MoE: Domain-Aware Mixture-of-Experts for PDEs with Multi-Regime Physics

arXiv:2609.07814v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) struggle on PDEs whose governing physics varies across the domain. We trace this to a structural property of st

Layer Selection in VLMs for Zero-Shot OOD Detection via Multi-Resolution Entropy Estimation

arXiv:2609.08524v1 Announce Type: new Abstract: Out-of-distribution (OOD) detection is crucial for safe deployment of medical AI systems, where domain shifts arise across institutions, acquisition pro

Layer-Wise Gate-Controlled Prompt Truncation in a Multimodal Chest X-Ray Classifier

arXiv:2609.06590v1 Announce Type: cross Abstract: Mixture of Prompt Experts (MoPE) adapts multimodal transformers through input-dependent prompt composition, while retaining a fixed prompt length. We

Tutorials

Learning Metamaterial Eigenmodes with Wavelet-Encoded Fourier Neural Operators

arXiv:2609.08102v1 Announce Type: new Abstract: Machine learning surrogates based on neural operators have shown broad applicability in solving forward PDE problems. However, eigenvalue problems, in w

tutorialsarxiv-cs-lg

Learning to Price and Stock Under Contextual and Censored Demand

arXiv:2609.06083v1 Announce Type: new Abstract: To make optimal joint pricing and inventory control decisions is a critical challenge for modern retailers. In practice, retailers face changing market

Leveraging Cardiac Imaging to Improve ECG-Based Detection of Chagas Disease in Resource-Constrained Settings

arXiv:2609.08582v1 Announce Type: new Abstract: Chagas disease is a major cause of cardiomyopathy in Latin America. Cardiac magnetic resonance (CMR) imaging can characterize its structural abnormaliti

Leveraging contextual events on structure-aware next activity prediction

arXiv:2609.08622v1 Announce Type: new Abstract: Predictive process monitoring aims at forecasting various aspects of running processes. Among the different tasks, next activity prediction represents t

applicationsarxiv-cs-lg

Localized Visual Feature Aggregation via Focus Pooling for Visuomotor Policies

arXiv:2609.08408v1 Announce Type: new Abstract: Focusing on spatially localized, control-relevant visual cues has been shown to improve data efficiency in visuomotor policies by reducing the need to m

local-aiarxiv-cs-ro

MAC-I^2: Learned Metrics-Aware Covariance for Robust Visual-Inertial Fusion in Initialization and Calibration

arXiv:2609.07116v1 Announce Type: new Abstract: Visual-Inertial (VI) fusion is fundamental to accurate and robust state estimation, where camera and IMU measurements are combined according to their re

local-aiarxiv-cs-ro

MamMA: A Mamba-Based Pedestrian Trajectory Prediction Algorithm Considering Occupancy Map and Pedestrian Awareness States

arXiv:2609.08041v1 Announce Type: new Abstract: Many pedestrian trajectory prediction algorithms have been proposed to improve the safety of navigation for mobile robots working in human-robot coexist

local-aiarxiv-cs-cv

Map the Possibilities: Spatial Belief Fields for Language-Goal Aerial Navigation

arXiv:2609.05841v1 Announce Type: new Abstract: Language-goal aerial navigation requires an agent to local- ize a potentially unobserved target from relational instruc- tions and partial observations,

local-aiarxiv-cs-cv