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GE-Act 2.0: Pretraining and Scaling a World-Action Model for Robotic Manipulation

arXiv:2609.05588v1 Announce Type: cross Abstract: World-action models (WAM) predict future states to guide robot actions, enabling learning from both action-free video and action-labeled interaction.

tutorialsarxiv-cs-cv

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Generalist Open-World Temporal Perception

DGX agent

arXiv:2609.06823v1 Announce Type: new Abstract: The next generation of artificial intelligence systems will likely be natively temporal and multimodal in both inputs and outputs: able to converse, per

researcharxiv-cs-cv

9 Sept 2026

Applications

Generalizable 6D Pose Estimation of Textureless Objects with Planar-based Gaussian Splatting

arXiv:2609.07231v1 Announce Type: new Abstract: Estimating the 6D pose of textureless objects without prior CAD models remains a critical challenge due to the lack of appearance features. While recent

applicationsarxiv-cs-ro

Generalized infinite dimensional Alpha-Procrustes based geometries

arXiv:2511.09801v3 Announce Type: replace-cross Abstract: This work extends the recently introduced Alpha-Procrustes family of Riemannian metrics for symmetric positive definite (SPD) matrices by inco

Generalizing HVAC Control With Domain Randomized Reinforcement Learning

arXiv:2609.05822v1 Announce Type: new Abstract: Deploying advanced HVAC (Heating, Ventilation and Air Conditioning) controllers at scale remains difficult because performance often depends on accurate

safetyarxiv-cs-lg

Generating from Discrete Distributions Using Diffusions: Insights from Random Constraint Satisfaction Problems

arXiv:2603.20589v2 Announce Type: replace Abstract: Generating data from discrete distributions is important for a number of application domains including text, tabular data, and genomic data. Several

Agents

Generation of Vectorized Maps Beyond Vehicle View

arXiv:2609.07511v1 Announce Type: cross Abstract: Autonomous driving relies on High Definition (HD) maps for safe navigation. Traditional HD maps construction is costly in hardware, data and human res

agentsarxiv-cs-lg

GenPuzzle: Benchmarking Visual Reasoning in Image Generation Models

arXiv:2609.05902v1 Announce Type: new Abstract: Recent image generation systems increasingly combine multimodal understanding, reasoning, and synthesis, suggesting that they may do more than render pl

GeoCo-SAVi: Geometry-Consistent Slot Attention for Explicitly Editable Object Representations

arXiv:2609.06628v1 Announce Type: new Abstract: Object-centric video models represent scenes with slots, yet exposed geometry can vary in meaning with appearance. In Invariant Slot Attention (ISA), ex

safetyarxiv-cs-cv

GeoContext: One Context Ladder, Two Failure Modes in Vision-Language Geolocation: Flat Reliance on User-Provided Location Context and False Confirmation of Location Claims

arXiv:2609.05761v1 Announce Type: new Abstract: Visual geolocation benchmarks typically ask a model where an image was captured without accounting for the location context that users often provide. We

Geodesic-informed Generative Diffusion Model For Topology-preserved Image Video Generation

arXiv:2609.08153v1 Announce Type: cross Abstract: Generative diffusion models have emerged as a class of powerful techniques for various imaging applications, including but not limited to synthesis, r

tutorialsarxiv-cs-cv

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

Geometric Distributional Control: Learning Progress with Partial Structural Knowledge

arXiv:2609.06331v1 Announce Type: new Abstract: Real-time control often sits between two limiting regimes. Predictive optimization and model-based control are powerful when dynamics, parameters, objec

safetyarxiv-cs-ro

Geometry-Aware Bayesian Parameter-Efficient Fine-Tuning on the Stiefel Manifold via Stein Variational Gradient Descent

arXiv:2609.08354v1 Announce Type: new Abstract: Several geometry-aware approaches to low-rank adaptation have emerged for parameter-efficient fine-tuning of large pre-trained models. These methods aim

Geometry-Aware Test-Time Learning for Quantitative Spatial Reasoning

arXiv:2609.06004v1 Announce Type: new Abstract: Quantitative spatial reasoning in visual-language models (VLMs) aims to infer spatial distances and directional relationships among objects in 3D space

researcharxiv-cs-cv

GIF: Agentic Generation of Interactive and Functional Object Compositions for Robot Learning

model-releasesarxiv-cs-ro

arXiv:2609.05927v1 Announce Type: new Abstract: Robot manipulation foundation models require scalable evaluation and data generation across diverse scenarios, with simulation providing an environment

GIFT: Goal-Injected Fine-Tuning for Efficient Manipulation Policy Adaptation

arXiv:2609.07006v1 Announce Type: new Abstract: Compared with relying solely on initial observations and language instructions, predicting goal images with generative models as high-level visual guida

safetyarxiv-cs-cv

GIFT: Reconciling Post-Training Objectives via Variational Finite-Temperature Gibbs Initialization

arXiv:2601.09233v3 Announce Type: replace Abstract: The prevailing post-training paradigm for Large Reasoning Models (LRMs)---Supervised Fine-Tuning (SFT) followed by Reinforcement Learning (RL)-suffe

GLoRI: Closed-Loop Whole-Body Tracking with Global-Local Reference Interaction for Humanoid Loco-Manipulation

arXiv:2609.05994v1 Announce Type: new Abstract: Humanoid loco-manipulation requires accurate whole-body motion tracking in the world frame for physical interaction. While local references preserve mot

safetyarxiv-cs-ro

GloVLA: Let Geometry Move and Local VLA Interact for Robust Object-Centric Manipulation in Unstructured Environments

model-releasesarxiv-cs-ro

arXiv:2609.06256v1 Announce Type: new Abstract: Vision-language-action (VLA) models have shown promising generalization for language-conditioned robot manipulation, but deploying them in unstructured

GoDeep: Annotation-Free Open-Vocabulary 3D Scene Understanding via Language-Space Lifting

arXiv:2609.09082v1 Announce Type: new Abstract: Open vocabulary 3D semantic segmentation methods typically lift CLIP features into 3D. This embeds points in a joint vision-language space known to beha

Local Ai

GOLF: Global Observation with Local Focus for Calibration-Aware Stereo Interaction Field Estimation

arXiv:2609.08607v1 Announce Type: new Abstract: We present GOLF, the first-place solution to the SHOW3D Interaction Field Estimation Challenge at HANDS@ECCV 2026. Given synchronized egocentric stereo

local-aiarxiv-cs-cv

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

GradeTrap: Authority Cues in Images Shift VLM Judgments Despite Explicit Instructions to Ignore Them

arXiv:2609.06058v1 Announce Type: new Abstract: As vision-language models (VLMs) become increasingly capable and are deployed in consequential real-world settings, they must evaluate evidence independ

GRAN-TED: Generating Robust, Aligned, and Nuanced Text Embedding for Diffusion Models

arXiv:2512.15560v3 Announce Type: replace Abstract: The text encoder is a critical component of text-to-image and text-to-video diffusion models, fundamentally determining the semantic fidelity of the

Applications

Granular-Ball Quantum Clustering for Resource-Efficient and Robust Learning

arXiv:2609.06016v1 Announce Type: new Abstract: Quantum clustering aims to exploit quantum feature representations to uncover complex data structures beyond conventional Euclidean geometry. Yet this s

applicationsarxiv-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

safetyarxiv-cs-ro

Graph neural networks and the energetic cavity method for combinatorial optimization

arXiv:2609.07456v1 Announce Type: cross Abstract: We study the use of graph neural networks (GNNs) for finding approximate ground states of Ising models. Efficiently finding these ground states is of

GraphFAS: A Distributed System for Automated Graph Feature Generation and Selection in Industrial Transaction Networks

arXiv:2609.08970v1 Announce Type: new Abstract: Industrial fraud detection often relies on costly expert-crafted features that overlook graph-structured relational signals, while GNNs often do not mee

GraphNOSE: A Graph Transformer in Olfaction

arXiv:2609.05694v1 Announce Type: new Abstract: Predicting olfactory qualities from molecular structure is an open problem in chemoinformatics. Although linear models can link molecular features to od

Grounded and Faithful P&ID Reasoning: Constraining Vision-Language Models with Recovered Evidence Graphs

arXiv:2609.05880v1 Announce Type: new Abstract: Piping and Instrumentation Diagrams (P&IDs) are the authoritative maps of process plants: isolation, maintenance, and HAZOP decisions depend on what con

GSComplete: Gaussian Splat Completion with 2D Diffusion Priors

arXiv:2609.08449v1 Announce Type: new Abstract: Gaussian splats provide a fast, high-fidelity representation for 3D objects but are often constructed from incomplete input data in practice, leaving mi

researcharxiv-cs-cv

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

Hardware Trojan Threats to Multi-Chiplet Photonic Neural Network Accelerators

arXiv:2609.06796v1 Announce Type: cross Abstract: Multi-chiplet photonic neural network accelerators (MCPNAs) combine photonic computation, photonic communica-tion, and heterogeneous chiplet integrati

Harnessing CLIP and DINO: An Uncertainty-Aware Cascaded Fusion Network for Generalizable Deepfake Image Detection

arXiv:2609.07670v1 Announce Type: new Abstract: The growing realism and accessibility of manipulated and generated faces threaten the trustworthiness of digital media. To detect such forgeries, deepfa

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

safetyarxiv-cs-lg

HealthLoopQA: A Context-Aware Question Answering Benchmark for Interpreting Wearable Monitoring Data in Diabetes Care

arXiv:2609.06976v1 Announce Type: new Abstract: As medical wearables become integrated into daily chronic disease care, effectively interpreting longitudinal monitoring data is essential for patients

Applications

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

Heat Kernel Textures: the Geodesic Gaussians That Do Not Splat

arXiv:2609.07557v1 Announce Type: new Abstract: 3D Gaussian Splatting has recently revolutionised novel view synthesis as well as many other 3D vision methods and applications. Drawing inspiration fro

researcharxiv-cs-cv

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

Agents

Hi-FLoop: Hierarchical State-Feedback Loops for Multi-Timescale World Modeling

arXiv:2609.08796v1 Announce Type: new Abstract: Multi-agent traffic simulation seeks diverse, coordinated, and physically realistic futures from maps and observed history. Long-horizon closed-loop gen

agentsarxiv-cs-cv

Agents

HiBRIDGE: A Hierarchical Bayesian Neural Network Framework for Interpretable Dialogue Management in Group-Robot Interaction

arXiv:2609.08678v1 Announce Type: new Abstract: In multi-party human-robot interaction, a robot must continuously decide whom to address and what to say to participate effectively in the conversation.

agentsarxiv-cs-ro

Hidden in Plain Sight: The Overlooked Significance of Canonical Elements for Extreme LLM Sparsity

arXiv:2609.06557v1 Announce Type: new Abstract: Large language models (LLMs) are often considered fragile under aggressive sparsification, and maintaining reliable performance typically requires stick

Hierarchical Fourier Approximation for Variational Quantum Distribution Learning

arXiv:2609.06307v1 Announce Type: cross Abstract: We study variational quantum distribution learning through a hierarchy of Walsh--Fourier approximations on the Boolean cube. At each level, a selected

Hierarchical Prompt Injector for Domain Generalization Segmentation

arXiv:2609.05864v1 Announce Type: new Abstract: Domain Generalized Semantic Segmentation (DGSS) is a challenging task, as vision models often rely on low-level appearance cues that change across domai

High-dimensional Linear Bandits with Knapsacks

arXiv:2311.01327v3 Announce Type: replace Abstract: We investigate the contextual bandits with knapsack (CBwK) problem in a high-dimensional linear setting, where the feature dimension can be very lar

High-Magnetization Sampling at Low Temperatures: Ising Models and Bayesian Sparse Linear Regression

arXiv:2609.08873v1 Announce Type: cross Abstract: Sparsity is a powerful structural resource in optimization and statistics. We develop frameworks for leveraging sparsity in sampling problems over the

tutorialsarxiv-cs-lg