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Geometric Identification in Predict-Then-Optimize Learning

arXiv:2609.33472v1 Announce Type: new Abstract: Decision-focused surrogates can recover downstream decisions without identifying the quotient report. We characterize the equality set of the convex Sma

Tutorials

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Geometric Inductive Biases for Semi-Supervised Equalization: The Constellation-Aware Transformer

DGX agent

arXiv:2609.33695v1 Announce Type: new Abstract: Decoding signals over unknown channels with minimal pilot overhead is a critical challenge in next-generation communications. Existing deep learning app

tutorialsarxiv-cs-lg

29 Sept 2026

Geometry-Adaptive Mechanisms for Private Synthetic Data

arXiv:2609.33363v1 Announce Type: cross Abstract: Generating differentially private synthetic data with meaningful Wasserstein utility guarantees is challenging in high dimensions. For datasets of siz

Geometry as Address: Routing Attention to Visual Memory for Long-Horizon Camera-Controlled Video Generation

arXiv:2609.34722v1 Announce Type: new Abstract: Long-horizon camera-controlled video generation requires recovering previously observed content from an ever-growing visual history. Existing approaches

Geometry-Aware Operator Families for Structured Representation Learning

arXiv:2609.33089v1 Announce Type: new Abstract: The geometry of latent representations governs which components should interact and how information should propagate, making geometry-aware operator des

Geometry-Preserving Blind Watermarking for Raw 3D Point Clouds

arXiv:2609.32222v1 Announce Type: new Abstract: Raw 3D point clouds are a core geometric representation. Establishing their ownership is challenging because point sets are irregular, unstructured, and

safetyarxiv-cs-cv

GeoShrink: Accelerating Diffusion Transformers with Two Lines of Code

arXiv:2609.33723v1 Announce Type: new Abstract: Diffusion transformers incur substantial inference cost through repeated model evaluations along a sampling trajectory. We introduce GeoShrink, a traini

GeoVerse: World-Consistent Novel View Synthesis in Geometric Latent Space

arXiv:2609.35734v1 Announce Type: new Abstract: Novel view synthesis from sparse images must reconcile faithful reconstruction of observed regions with plausible completion of unseen content, while ma

GERIS: A Game-Theoretic Framework for Filtering Instance-Dependent Label Noise in License Plate Data Augmentation

arXiv:2609.31731v1 Announce Type: new Abstract: In this paper, we propose GERIS, a game-theoretic framework for instance selection in the data augmentation phase of license plate recognition systems.

applicationsarxiv-cs-cv

Getting Motif-ated: Controllable AI Compositions from Injected Motif Prompts

arXiv:2609.32788v1 Announce Type: new Abstract: Deep learning has transformed symbolic music generation by borrowing the training paradigms of large language models, with systems such as NotaGen now p

GLF-Q: Global-Local Feature-based Quantization for Vision Transformers

arXiv:2609.34564v1 Announce Type: new Abstract: Post-training quantization (PTQ) efficiently compresses Vision Transformers (ViTs) without retraining, yet suffers severe accuracy degradation at low bi

safetyarxiv-cs-cv

GlowTact: Simple and Compact Vision-Based Tactile Sensing with High Sensitivity and Spatial Resolution

arXiv:2609.32471v1 Announce Type: new Abstract: Vision-based tactile sensors (VBTS) provide rich contact information for robotic manipulation, but existing designs can be hard to simplify and adapt to

researcharxiv-cs-ro

Goal-Conditioned Supervised Learning for Multi-Objective Recommendation

arXiv:2412.08911v4 Announce Type: replace Abstract: Multi-objective learning endeavors to concurrently optimize multiple objectives using a single model, aiming to achieve high and balanced performanc

GPARA: Graph-Posterior-Aligned Refinement and Active Acquisition for Grounding Diffusion Priors

arXiv:2609.34172v1 Announce Type: new Abstract: Active grounding of a frozen diffusion prior requires jointly determining where new measurements should be taken and how they should be used to refine t

Gradient-Guided Decoupled Adaptation for Geospatial Vision-Language Models

arXiv:2609.32737v1 Announce Type: new Abstract: Existing geospatial vision-language models (Geo-VLMs) typically optimize diverse geospatial tasks through a unified multi-task adaptation paradigm witho

Gradients for Interventions and Activations for Detection: Targeted Feature Learning in Language Models

arXiv:2609.32355v1 Announce Type: cross Abstract: Model-internal features can be studied through both their ability to identify a specified concept and their causal effect when manipulated, e.g., thro

GradLev: Token-Parallel Test-Time Training Via Costate Prediction

arXiv:2609.34174v1 Announce Type: new Abstract: Test-time training (TTT) allows a model to improve its predictions at inference time by updating weights after every observed token. However, sequential

Local Ai

Graph-Based Learning for Multi-Horizon Martian Atmospheric Forecasting

arXiv:2609.35042v1 Announce Type: cross Abstract: Martian weather forecasting is important for future exploration, but atmospheric behaviour on Mars combines spatial, temporal, vertical, and dust-driv

local-aiarxiv-cs-lg

Graph-Based Simultaneous Path and Foothold Planning for Multi-Limbed Intra-Vehicular Robots in Space Stations

arXiv:2609.35000v1 Announce Type: new Abstract: Robot-aided operations in space stations are essential for reducing the workload of astronauts and improving the efficiency of on-orbit activities. Mult

researcharxiv-cs-ro

Graph Forward Distribution Matching for Molecular Inverse Design

arXiv:2609.32056v1 Announce Type: new Abstract: Achieving precise control over multiple properties without sacrificing chemical validity remains a central challenge in molecular inverse design. Existi

Graph Memory: Spectral Associative Memory via Dirichlet Energy

arXiv:2609.32365v1 Announce Type: new Abstract: Dense associative memories have traditionally focused on storing and retrieving vector-valued patterns. Many modern machine learning problems, however,

applicationsarxiv-cs-lg

Graph Structure Learning with Temporal Graph Information Bottleneck for Inductive Representation Learning

arXiv:2508.14859v2 Announce Type: replace Abstract: Temporal graph learning is crucial for dynamic networks where nodes and edges evolve over time and new nodes continuously join the system. Inductive

applicationsarxiv-cs-lg

Graph World Models for Constrained Epidemic Policy Planning

arXiv:2609.35545v1 Announce Type: new Abstract: Epidemic policy planning often requires coordination between geographical regions, taking into account mobility-driven spillovers and how to make use of

Graph Your Own Prompt

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,

GraphHCA: Closed-Form Hindsight Credit Assignment for Long-Horizon LLM Agents

arXiv:2609.35084v1 Announce Type: new Abstract: Group-based reinforcement learning (RL) has advanced large language models (LLMs) and is increasingly extending to agentic tasks, where sparse terminal

GraphSelect for Budgeted Representation Selection in Multimodal Graph Inference

arXiv:2609.33561v1 Announce Type: new Abstract: Multimodal graph predictors combine text, images, and relations to classify connected entities. How much of this input is needed to preserve their predi

Grasp2Twist: Learning Bimanual Dexterous Jar Opening by Reinforcement Learning

arXiv:2609.32064v1 Announce Type: new Abstract: This paper presents Grasp2Twist, a bimanual dexterous manipulation system that learns to grasp and twist open jar lids using reinforcement learning. Lea

safetyarxiv-cs-ro

Gravity Falls: A Comparative Analysis of Domain-Generation Algorithm (DGA) Detection Methods for Mobile Device Spearphishing

arXiv:2603.03270v2 Announce Type: replace-cross Abstract: Mobile devices are frequent targets of eCrime threat actors through SMS spearphishing (smishing) links that leverage Domain Generation Algorit

Hardware

Greenpixie's AI Token Methodology: Assessing the Energy, Water and CO_2ext{-eq} Impact of AI Tokens for Open and Closed Weight Models

arXiv:2609.33965v1 Announce Type: cross Abstract: We describe a methodology for estimating the per-token energy cost of cloud-hosted large language model (LLM) inference, separating between input (pre

hardwarearxiv-cs-lg

Grounding Vision-Language Models in Driving Semantics: A Multi-Dataset Predicate Framework for Explainable Reasoning

arXiv:2609.31636v1 Announce Type: cross Abstract: Vision-language models are increasingly used for driving-scene understanding, yet the semantic relations expressed in their outputs are often difficul

GroupMask: Layer-Adaptive Group-wise Sparsity for Semi-Structured LLM Pruning

arXiv:2609.33977v1 Announce Type: new Abstract: Semi-structured pruning compresses large language models (LLMs) while keeping a regular sparse structure, but the prevailing N:M pattern fixes the same

Groupwise Agentic Grading and Advantage Redistribution for Code Agent RL

arXiv:2609.32577v1 Announce Type: cross Abstract: Reinforcement learning (RL) for code agents often uses executable tests to provide binary rewards. With these rewards, Group Relative Policy Optimizat

Groupwise Selective State-Space Filtering for Accurate and Streaming Action Boundary Detection

arXiv:2609.33400v1 Announce Type: new Abstract: Action boundary detection partitions untrimmed video into intervals without assigning action classes. We present a boundary-detection adapter operating

Tutorials

GT-PSSM: Unified Probabilistic Framework for Stochastic Dynamics Modeling and Dependency Learning in Multivariate Time Series Anomaly Detection

arXiv:2609.34161v1 Announce Type: cross Abstract: Multivariate time series anomaly detection (MTAD) is crucial for ensuring the safe and reliable operation of complex systems. Many existing methods le

tutorialsarxiv-cs-lg

GT-VLA: Target-Conditioned Trace Guidance for Generalizable Robotic Manipulation

arXiv:2609.31904v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown strong performance on robotic manipulation, but they often struggle to generalize to unseen tasks, conf

GTRL: Grounding Divide-and-Conquer Value Learning with Temporal Differences

arXiv:2609.33259v1 Announce Type: new Abstract: In offline goal-conditioned reinforcement learning (GCRL), divide-and-conquer scales to long horizons by joining two shorter segments at a subgoal. Howe

Local Ai

GuardPIBT: Counterfactually Gated Neural Guidance for Ultra-Large-Scale 3D Multi-Agent Path Finding

arXiv:2609.35267v1 Announce Type: new Abstract: Large-scale 3D multi-agent path finding becomes increasingly difficult under dense traffic. Priority Inheritance with Backtracking (PIBT) scales well, b

local-aiarxiv-cs-ro

Agents

Guava: Distilling Frontier VLM Agents into a Compact Model with a Manipulation Harness

arXiv:2606.18363v2 Announce Type: replace Abstract: Language models trained on large-scale vision-language data have demonstrated strong potential for embodied agents. Harnessing models through embodi

agentsarxiv-cs-ro

GUI-GenBench: Evaluating Image Generation Models as Interactive GUI Environments

arXiv:2602.09007v3 Announce Type: replace-cross Abstract: An image generation model used as a graphical user interface (GUI) environment must produce not only a plausible screen but also the correct r

Agents

GUIDE-FBO: Guidance via Uncertainty Intervention and Distributional Exchange for Federated Bayesian Optimization

arXiv:2609.35038v1 Announce Type: cross Abstract: Federated Bayesian Optimization (FBO) enables distributed agents to collaboratively optimize expensive black-box objectives without sharing raw local

agentsarxiv-cs-lg

HAGI++: Head-Assisted Gaze Imputation and Generation

arXiv:2511.02468v2 Announce Type: replace-cross Abstract: Mobile eye-tracking is crucial for capturing human visual attention in real-world and XR settings, supporting research and human-computer inte

applicationsarxiv-cs-cv

HALO: Enhancing Time Series Generation via Hyperspherical Latents and Masked AutoregRessive Modeling

arXiv:2609.34511v1 Announce Type: new Abstract: Most existing time series generators rely on a two-stage modeling paradigm: the first stage learns discrete latent representations of time series; the s

Local Ai

HamiFormer: Dual-Expert Diffusion Fields with Affine Symplectic Maps

arXiv:2609.32838v1 Announce Type: new Abstract: Predicting smooth dynamics and collisions requires modeling continuous evolution and abrupt state changes. We introduce HamiFormer, a dual-expert diffus

local-aiarxiv-cs-lg

Hamiltonian JEPA: Action-Conditioned World Models with an Inherited Control State

arXiv:2609.33497v1 Announce Type: new Abstract: Planning from pixels needs more than a latent space that is stable and predictable. The state the planner scores must also be organized by how actions m

Handwritten Digit Leakage from Smartphone Motion Sensors Across Unseen Users and Phone Models

arXiv:2609.32117v1 Announce Type: new Abstract: Smartphone motion sensors support interactive applications, but their readings may also reveal touchscreen input beyond their intended use. Assuming kno

Handwritten Text Recognition Lives in the High-Pixel Variance Subspace

arXiv:2609.35473v1 Announce Type: new Abstract: In self-supervised pretraining for Handwritten Text Recognition (HTR), pixel reconstruction methods outperform contrastive methods, unlike in natural-im

HapticWorld: an Interactive World Simulator with Real-time Torque Feedback

arXiv:2609.31924v1 Announce Type: new Abstract: Contact-rich manipulation depends on force sensing that is hard to infer from visual signals alone, both for collecting demonstrations and for training

safetyarxiv-cs-ro

Hard Vision, Easy Vision: What GPT-6 Astra Reveals Across Computer Vision

arXiv:2609.35718v1 Announce Type: new Abstract: Frontier general-purpose systems are rapidly expanding beyond visual understanding into capabilities traditionally handled by dedicated computer-vision