Search: “framework”

Behavioral Foundation Models for Quality Diversity

arXiv:2609.35615v1 Announce Type: new Abstract: Behavioral Foundation Models (BFMs) are an emerging paradigm in reinforcement learning, playing a role analogous to large language models in natural lan

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Beyond Geometry: Benchmarking and Consistency Reasoning for 3D Logical Anomaly Detection

DGX agent

arXiv:2609.34143v1 Announce Type: new Abstract: Existing 3D industrial anomaly detection mainly targets local geometric deviations. In contrast, many industrial anomalies violate object-level design o

model-releasesarxiv-cs-cv

29 Sept 2026

BR-MPPI: Barrier-Rate Guided MPPI for Enforcing Multiple Inequality Constraints with Learned Signed Distance Fields

model-releasesarxiv-cs-ro

arXiv:2506.07325v2 Announce Type: replace Abstract: Model Predictive Path Integral (MPPI) control provides a sampling-based framework for optimal control, while Control Barrier Functions (CBFs) provid

Bregman geometry-aware split Gibbs sampling for Bayesian Poisson inverse problems

arXiv:2511.12257v2 Announce Type: replace-cross Abstract: This paper proposes a novel Bayesian framework for solving Poisson inverse problems by devising a Monte Carlo sampling algorithm which account

Safety

Contextual Distributionally Robust Optimization with Causal and Continuous Structure

arXiv:2601.11016v3 Announce Type: replace-cross Abstract: We propose a framework for contextual distributionally robust optimization (DRO) that considers the causal and continuous structure of the und

safetyarxiv-cs-lg

D-JEPA: Design-Recoverable JEPA Representation with Swappable Physics Decoders

arXiv:2609.33110v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPAs) provide a framework for learning compact representations without directly reconstructing high-dimension

DiffPTS: Rethinking Diffusion ELBO for Probabilistic Time Series Forecasting

arXiv:2609.32363v1 Announce Type: new Abstract: Probabilistic time series forecasting requires modeling and predicting complex and time-varying distributions. Recently, Denoising Diffusion Probabilist

Disciplined Biconvex Programming

arXiv:2511.01813v3 Announce Type: replace-cross Abstract: We introduce disciplined biconvex programming (DBCP), a modeling framework for specifying and solving biconvex optimization problems. Biconvex

DPAMixerSR: An Efficient Degradation-Pattern-Aware Model for Image Super-Resolution

arXiv:2609.32705v1 Announce Type: new Abstract: While content-adaptive schemes have delivered notable advances in image super-resolution (SR), existing approaches typically focus on texture complexity

Enhancing generalization in endwall film cooling prediction: Incorporating the superposition principle into transformer-based neural operators

arXiv:2609.31633v1 Announce Type: new Abstract: In this study, a physics-enhanced neural operator framework is proposed to enhance the generalization prediction ability of the cooling layout of a turb

FloodDiffusion 2: Efficient and Path Controllable Streaming Motion Generation

arXiv:2609.33167v1 Announce Type: new Abstract: We present FloodDiffusion 2 (FD2), an efficient and controllable framework that builds upon FloodDiffusion (FD1), a state-of-the-art streaming motion ge

applicationsarxiv-cs-cv

Agents

FlowAct-R2: Beyond Talking Avatar via Streaming Multimodal References and Proactive Agent Planning

arXiv:2609.35728v1 Announce Type: new Abstract: We present FlowAct-R2, a framework for interactive humanoid video generation that combines continuous multimodal control with proactive agent planning.

agentsarxiv-cs-cv

GAUGE: Planner-Conditioned Active Calibration of Opaque Quadruped Velocity Interfaces

arXiv:2609.32154v1 Announce Type: new Abstract: In this paper, we present a Goal-Aware Uncertainty-Guided Exploration (GAUGE) framework for planner-conditioned active calibration of opaque quadruped v

researcharxiv-cs-ro

Graph Your Own Prompt

model-releasesarxiv-cs-cv

arXiv:2509.23373v3 Announce Type: replace-cross Abstract: We propose Graph Consistency Regularization (GCR), a novel framework that injects relational graph structures, derived from model predictions,

Safety

Hierarchical Multi-agent Reinforcement Learning for Warehouse Robot Coordination under Communication Loss

arXiv:2609.33637v1 Announce Type: cross Abstract: In this paper, we propose a hierarchical multi-agent reinforcement learning framework for coordinating robot teams in warehouse environments under com

safetyarxiv-cs-ro

In-game Toxic Detection: Bi-directional Representations with Attention Residuals

arXiv:2609.34584v1 Announce Type: cross Abstract: In-game toxic language has emerged as a critical concern in the gaming industry and community. While several frameworks and models for online game tox

applicationsarxiv-cs-lg

Information-Theoretic Analysis of Next-Token Prediction under Markovian Data

arXiv:2609.34731v1 Announce Type: cross Abstract: We develop an information-theoretic framework for generalization in next-token prediction under temporally dependent data. We consider independent tra

Agents

Interactive Distributionally Robust Multi-Agent Learning with General Function Approximation

arXiv:2609.32048v1 Announce Type: new Abstract: Model misspecification poses a fundamental challenge in multi-agent reinforcement learning, where transition uncertainty can be amplified by strategic i

agentsarxiv-cs-lg

Knowledge-Driven XRD Phase Identification via Multi-View Retrieval and Explanation

arXiv:2609.31888v1 Announce Type: cross Abstract: X-ray diffraction (XRD) is a experimental technique for determining the phase composition and structure of crystalline materials. However, interpretin

Lagrangian--Hamiltonian Flows for Video Prediction and Image Generation: A Symplectic Perspective

arXiv:2609.35710v1 Announce Type: new Abstract: We introduce LHFM, a geometric framework for learning image dynamics. Drawing on structures central to classical mechanics, symplectic geometry, and geo

Local Ai

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

local-aiarxiv-cs-cv

LQR-ArUco Fusion: Robust Hierarchical Control for Navigation and Asymmetric Manipulation in Two-Wheeled Robots

arXiv:2609.35700v1 Announce Type: new Abstract: We propose a hierarchical control framework to address severe dynamic instabilities and navigational drift that arise when a two-wheeled inverted pendul

researcharxiv-cs-ro

LTV-CTDNet: Compositional Turning Decomposition for Short-Term Turning-Movement Forecasting

arXiv:2609.34014v1 Announce Type: new Abstract: Short-term turning-movement forecasts can support signal control and corridor operations, but unconstrained neural networks may produce physically impos

MultiEcho: An Experimental Science of Learned Worlds

arXiv:2609.33347v1 Announce Type: new Abstract: World models can be studied as experimental systems with response laws of their own. We introduce MultiEcho, a framework for estimating these laws throu

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

PI-NOMT: Physics-Informed Neural Optimal Mass Transport for Brain Fluid Dynamics

arXiv:2609.33857v1 Announce Type: new Abstract: Recovering hidden transport mechanisms from sparse spatiotemporal observations is a fundamental inverse problem in scientific machine learning. In brain

Safety

Predictive Semantic Safety: From Visual Physical Reasoning to Safety-Critical Control

arXiv:2609.34356v1 Announce Type: cross Abstract: Physical interactions can create future hazards that are not apparent from the robot's current geometric surroundings. We present a framework termed P

safetyarxiv-cs-lg

Probabilistic Geodesic Flow Matching on Location-Scale Families

arXiv:2609.34613v1 Announce Type: cross Abstract: Flow matching (FM) has recently emerged as a promising framework for generative modeling due to its conceptual simplicity and strong empirical perform

ProDyGS: Dynamic Gaussian Splatting from a Single Static Monocular Camera

arXiv:2609.32711v1 Announce Type: new Abstract: We present ProDyGS, a novel dynamic 3D Gaussian Splatting framework for high-quality novel view synthesis from videos captured by a single static camera

Quantifying Behavioral Tails in Black-Box Language Models

arXiv:2609.33638v1 Announce Type: new Abstract: We introduce RareTrap, a framework for estimating the probability of severe behaviors in black box large language models (LLMs). A key challenge for pro

R2T: Rule-Encoded Loss Functions for Sequence Tagging in Low-Resource Languages

arXiv:2510.13854v2 Announce Type: replace-cross Abstract: We introduce Rule-to-Tag (R2T), a framework that turns linguistic rules into the training signal for neural sequence taggers in low-resource l

Residual Learning-Based Control of Vehicle Platoons with ell_2 Stability Guarantees via Recurrent Equilibrium Networks

arXiv:2609.33892v1 Announce Type: new Abstract: This paper proposes a residual learning-based control framework for heterogeneous vehicle platoons subject to parametric uncertainty and external distur

researcharxiv-cs-ro

Local Ai

ResonAct: Streaming Metrics for Runtime Diagnosis and Self-Healing in Multi-Agent Systems

arXiv:2609.34701v1 Announce Type: cross Abstract: Multi-agent systems (MAS) are increasingly used to automate enterprise workflows involving multiple specialized agents, external tools, and long-runni

local-aiarxiv-cs-lg

Robust Bayesian Optimization with Q-Exponential Surrogates

arXiv:2609.32775v1 Announce Type: new Abstract: Bayesian optimization (BO) is a widely used framework for optimizing expensive black-box objectives, but standard BO methods often use Gaussian process

Simulation-Based Quantum System Inference with Neural Posterior Estimation

arXiv:2609.34995v1 Announce Type: cross Abstract: Models of quantum systems faithfully map system parameters to observations, but the inverse problem of parameter inference from measurement data prese

Hardware

Spexis: Speculative Lookahead Scheduling for LLM Inference

arXiv:2609.34370v1 Announce Type: new Abstract: Spexis is a multi-GPU LLM inference framework that improves the efficiency of pipeline and tensor parallelism through speculative parallelism. Rather th

hardwarearxiv-cs-lg

Squeeze3D: Extreme Neural Compression with Latent Space Bridging

arXiv:2506.07932v2 Announce Type: replace-cross Abstract: We propose Squeeze3D, a novel framework that leverages implicit prior knowledge learnt by existing pre-trained encoders and decoders to compre

STAR: Adaptive Spatial-Temporal Normalization for Unified Microservice Incident Management

arXiv:2609.31645v1 Announce Type: new Abstract: Automated incident management in large-scale microservice systems relies on learning robust representations from multimodal observability data, includin

applicationsarxiv-cs-lg

Structuring Relations Among Learning Paradigms via Protocol--Objective--Resource Reductions

arXiv:2609.32766v1 Announce Type: new Abstract: Modern machine learning spans supervised, transfer, continual, meta-learning, and related regimes that often reuse the same hypothesis classes, architec

Agents

TAO-DA: Towards Autonomous Operation--A Dual-Arm Vision-Language-Action Model for Coordinated Manipulation

arXiv:2609.33197v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models provide a unified framework for grounding high-level semantic information into low-level robot actions, enabling sca

agentsarxiv-cs-ro

Test-Time Spatial Reasoning for Robot Manipulation Using Generative Real-to-Sim

model-releasesarxiv-cs-cv

arXiv:2609.33982v1 Announce Type: cross Abstract: Spatial reasoning is fundamental to general robot intelligence, as it enables robots to complete long-horizon tasks involving multi-object interaction

THEIA: A Multimodal Dataset and Benchmark for Vision-Language Analysis of Layout

arXiv:2609.35035v1 Announce Type: new Abstract: The integration of artificial intelligence into computer-aided design frameworks has sparked a shift in the design of analog integrated circuits (ICs),

Theoretical Refinement of CLIP by Utilizing Linear Structure of Optimal Similarity

arXiv:2510.15508v2 Announce Type: replace Abstract: In this study, we propose an enhancement to the similarity computation mechanism in multimodal contrastive pretraining frameworks such as CLIP. Prio

Tilted Schrodinger Bridge Matching

arXiv:2609.34642v1 Announce Type: new Abstract: Schrodinger bridges provide an entropy-regularized framework and a principled solution for unpaired domain translation. In practice, a pretrained bridge

Unifying Distributional Training for One-Step Visual Generation

arXiv:2609.35763v1 Announce Type: new Abstract: Distributional training provides collective supervision for one-step visual generation by matching real and generated features in frozen representation

Universal Dynamic Portfolios

arXiv:2609.34643v1 Announce Type: new Abstract: Cover's Universal Portfolio (Cover, 1991) matches the performance of the best constant rebalanced portfolio in hindsight. We generalize this framework t

Video Captioning in Low-Light Conditions through Efficient Uncertainty-Aware Caption Correction

arXiv:2609.31697v1 Announce Type: new Abstract: Low-light conditions can significantly degrade the ability of vision-language models (VLMs) to accurately describe human actions in videos. In this work

applicationsarxiv-cs-cv

World SLAM Model: Joint World Modeling for SLAM and Navigation

arXiv:2609.32626v1 Announce Type: cross Abstract: We introduce World SLAM Model (WSM), a unified framework that brings the SLAM paradigm directly into downstream navigation. Rather than treating SLAM