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GameSmith: Scaling Zero-Sum Self-Play with Synthesised Games

arXiv:2610.13995v1 Announce Type: new Abstract: Post-training large language models (LLMs) on two-player zero-sum games provides a verifiable reward, and the gains have been shown to transfer to gener

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Gaussian Process Bandits for AI System Optimization with Selectively Verified Feedback

DGX agent

arXiv:2610.17760v1 Announce Type: new Abstract: Gaussian process bandits exploit similarities among configurations to optimize prompts, retrieval systems, and agent workflows. In these applications, h

agentsarxiv-cs-lg

14 Oct 2026

Gaussian Splatting for Real-Time Scene Reconstruction: Methods, Systems, and Trade-offs

arXiv:2610.17513v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) allows for high-quality real-time novel-view synthesis. Since its inception in 2023, its explicit and highly configurable s

Gen Through the Lens: Camera-Controllable Video Generation via Cross-Coordinate Conditioning Fusion

arXiv:2610.15900v1 Announce Type: new Abstract: We present Gen Through the Lens, a camera-controllable image-to-video generation framework that synthesizes videos from a given reference image while en

tutorialsarxiv-cs-cv

Applications

Generalizable Model Editing Could Be More Than Direct Generalization

arXiv:2610.15707v1 Announce Type: new Abstract: A central desideratum in model editing is generalization to complex tasks, which prior work formalizes under a direct generalization paradigm: treating

applicationsarxiv-cs-lg

Generalized PINN-Based Inverse Estimation of Spatially Varying Heat Transfer Coefficients with Transfer Learning

arXiv:2610.14008v1 Announce Type: new Abstract: This study investigates generalized boundary representations and transfer learning for physics-informed neural-network (PINN) estimation of spatially va

Generative AI for Autonomous Driving: A Review

arXiv:2505.15863v2 Announce Type: replace Abstract: Generative AI (GenAI) is rapidly advancing the field of Autonomous Driving (AD), extending beyond traditional applications in text, image, and video

Generative Conformal Prediction with Optimized Coverage Allocation

arXiv:2410.13735v3 Announce Type: replace Abstract: Conformal prediction provides model-agnostic uncertainty quantification with guaranteed coverage, but conventional methods often yield overly conser

Generative Flow on Symbolic Abstractions for Embodiment Capability Discovery

arXiv:2610.17174v1 Announce Type: cross Abstract: Achieving complex, long-horizon robot behavior remains challenging because successful execution depends on skills grounded in a robot's physical affor

safetyarxiv-cs-lg

Generative Models as Adaptive Trust Regions for Discrete Bayesian Optimisation

arXiv:2610.16992v1 Announce Type: new Abstract: Bayesian optimisation (BO) is a powerful framework for sample-efficient optimisation of expensive black-box functions, but its application to high-dimen

Generative Quantum Machine Learning Methods for Cancer Detection using Augmented Datasets

arXiv:2610.15110v1 Announce Type: cross Abstract: Cancer detection using AI methods and image databases faces several challenges, including limited and imbalanced image datasets, long algorithm traini

Genesis: Visual Augmentation Primitives for Multimodal Chain-of-Thought Reasoning

arXiv:2610.15565v1 Announce Type: new Abstract: Recent multimodal large language models achieve promising results on visual reasoning tasks, approaching human-level performance on existing STEM benchm

GeoBridge: Evolving Transferable Decoder Topologies for Geometric Vision

arXiv:2610.15280v1 Announce Type: new Abstract: Depth estimation and Gaussian reconstruction share a need for multi-scale feature processing, yet use different prediction interfaces and training objec

GeoFix: Geometry Fixing for 4D Consistent Generation

arXiv:2610.14293v1 Announce Type: new Abstract: Video diffusion models increasingly serve as priors for 4D generation, but the generated videos often lack geometric consistency. Recent approaches addr

GeoMER: A Joint Euclidean-Hyperbolic Geometry Framework for Multimodal Emotion Recognition

arXiv:2610.18587v1 Announce Type: cross Abstract: Multimodal Emotion Recognition (MER) aims to understand human emotions by integrating information from multiple modalities such as speech and text. Ps

Geometric Calibration of Supervised Fine-Tuning

arXiv:2610.18634v1 Announce Type: new Abstract: Recent studies investigate the weight geometry through its spectral structure, which characterizes how the weights transform different input directions.

Geometric Parrots: Rule Absence vs. Rule Fragility in Spatial and Physical Reasoning for Vision-Language Models

arXiv:2610.16170v1 Announce Type: new Abstract: Vision-language models (VLMs) can answer many geometric and physical reasoning questions correctly, yet still behave inconsistently in interaction, for

Geometric Structure Predicts Per-Example Neighborhood Loss Under PCA Truncation

arXiv:2610.17742v1 Announce Type: cross Abstract: Dimensionality reduction can preserve the average performance of text embeddings even when a substantial fraction of their dimensions is removed. Aggr

safetyarxiv-cs-lg

Geometry-Aware Predictive Control for Walk-to-Run Bipedal Obstacle Crossing

model-releasesarxiv-cs-ro

arXiv:2610.15735v1 Announce Type: new Abstract: This paper presents a geometry-aware predictive control framework for bipedal obstacle crossing across walking and running regimes. The proposed approac

Geometry-Guided Semantic Reconstruction for 3D Instance Segmentation

arXiv:2610.16122v1 Announce Type: new Abstract: 3D instance segmentation requires representations that are both geometrically structured and semantically discriminative. Pure 3D encoders model spatial

GeoMotionGPT: Geometry-Aligned Motion Understanding with Large Language Models

arXiv:2601.07632v5 Announce Type: replace Abstract: Discrete motion tokenization has recently enabled Large Language Models (LLMs) to serve as versatile backbones for motion understanding and motion-l

GeoNIRS: Geometry-Aware Pretraining for Heterogeneous fNIRS Representation Learning

arXiv:2610.17845v1 Announce Type: new Abstract: Functional near-infrared spectroscopy (fNIRS) provides portable and spatially localized measurements of cortical hemodynamics, but differences in channe

local-aiarxiv-cs-lg

GeoReader: Learning Latent Geometry for Spatial Reasoning in Vision-Language Models

arXiv:2610.18694v1 Announce Type: new Abstract: Vision-language models (VLMs) struggle with metric and multi-view relationships that remain implicit in RGB observations. Geometry foundation models rec

Getting Space Right: Agentic Rewards for Image Generation

arXiv:2610.14852v1 Announce Type: new Abstract: Reinforcement learning (RL) is promising for spatial text-to-image generation, but existing work largely focuses on policy optimization, assuming accura

Applications

GG-Nav: Goal-oriented Grounding Chain-of-Thought Elicits Reasoning in Navigation Foundation Models

arXiv:2610.14541v1 Announce Type: new Abstract: Emerging strong Vision-Language Models (VLMs) have advanced navigation foundation models. However, these models still have unsatisfactory performance on

applicationsarxiv-cs-ro

GHOST: Geometry-Constrained Hybrid Diffusion for Open-Vocabulary 3D Scene Graph Generation

arXiv:2610.16455v1 Announce Type: new Abstract: 3D scene graph generation requires understanding both object semantics and metric spatial relations. However, existing open-vocabulary methods often str

tutorialsarxiv-cs-cv

GIFT-Eval-CTX: A Benchmark For Contextual Forecasting Model Evaluation

arXiv:2610.17794v1 Announce Type: new Abstract: Contextual forecasting seeks to improve time series forecasting by incorporating forward-looking information, such as planned events, external condition

GIFT: Global Irreplaceability Frame Targeting for Efficient Video Understanding

arXiv:2603.25072v2 Announce Type: replace Abstract: Video Large Language Models (VLMs) have achieved remarkable success in video understanding, but the significant computational cost from processing d

Global Disaster Risk Assessment Using World Risk Index Data: A Geospatial and Visual Analytics Approach

arXiv:2610.15064v1 Announce Type: new Abstract: The world has seen several threats that include resource depletion, food security, poverty and inequality, difficulties associated with urbanization, mi

Global Optimality of Pose Graph Optimization

arXiv:2610.14655v1 Announce Type: new Abstract: Pose Graph Optimization (PGO) is a classical and widely applied problem in state estimation for robotics, playing a fundamental role in localization, ma

researcharxiv-cs-ro

Agents

GLST: Global-Local Spatio-Temporal Memory Decomposition Framework for Online Chained-Goal Navigation

arXiv:2610.17927v1 Announce Type: new Abstract: Autonomous navigation in real-world environments often requires long-horizon operation under partial observability and evolving goals. Existing mapless

agentsarxiv-cs-ro

Gluing Local Contexts into Global Meaning: A Sheaf-Theoretic Decomposition of Transformer Representations

arXiv:2610.17117v1 Announce Type: cross Abstract: Existing interpretability tools do not test whether a representation keeps the same content when only the phrasing changes. We treat each paraphrase p

local-aiarxiv-cs-lg

GNFormer: Gaussian Neural Field Transformer for Efficient Camera-based Occupancy Prediction

arXiv:2610.15522v1 Announce Type: cross Abstract: Camera-based occupancy prediction provides geometric and semantic scene understanding for robot perception and has been adopted in autonomous vehicle

GpFlash: Maximizing Speed and Minimizing Memory for Gaussian Process Training and Prediction

arXiv:2610.16861v1 Announce Type: new Abstract: This paper presents GpFlash, a Gaussian process library that is focused on fast training and posterior evaluations, minimal memory usage, and scalabilit

tutorialsarxiv-cs-lg

GPU Goldmines: Tunable WebGPU Kernels for Edge LLM Inference

arXiv:2610.17321v1 Announce Type: cross Abstract: As demand for LLM inference grows and consumer GPUs grow more capable, edge deployment is becoming increasingly attractive. WebGPU is compelling in th

Grables: When Graph Structure Helps Tabular Prediction

arXiv:2602.03945v2 Announce Type: replace Abstract: Simple row-wise predictors that score each row independently remain competitive with far more expressive architectures on tabular benchmarks, which

Gradient Routing Localizes and Removes Unintended Behaviors in RL

arXiv:2610.17062v1 Announce Type: new Abstract: We propose a mitigation to reward hacking in reinforcement learning. Our setup involves a misspecified reward function that gives rise to unintended beh

tutorialsarxiv-cs-lg

Graph Metanetworks for Transformer Based Language Models

arXiv:2610.18471v1 Announce Type: new Abstract: Weight-space learning treats the weights of neural networks as data, processed by other models called metanetworks. A key challenge is that different we

Agents

Graph Neural Network-Based Reinforcement Learning for Controlling Biological Networks - the GATTACA Framework

arXiv:2505.02712v4 Announce Type: replace Abstract: Cellular reprogramming, the artificial transformation of one cell type into another, has been attracting increasing research attention due to its th

agentsarxiv-cs-lg

Graph3R: Unifying View Graph Initialization with Feed-Forward Reconstruction

arXiv:2610.16272v1 Announce Type: new Abstract: Feed-forward reconstruction recovers camera poses and dense geometry from image sets whose views are assumed to come from a single scene. In practice, u

local-aiarxiv-cs-cv

GREAT: A Graph Edge Attention Network for the Electric Vehicle Routing Problem with Asymmetric Costs

arXiv:2408.16717v4 Announce Type: replace Abstract: Due to the ongoing electrification of transportation systems, energy-based routing problems such as the Electric Vehicle Routing Problem (EVRP) are

Greedy Heuristics for Sampling-Based Motion Planning in High-Dimensional State Spaces

arXiv:2405.03411v5 Announce Type: replace Abstract: Informed sampling techniques accelerate the convergence of sampling-based motion planners by biasing sampling toward regions of the state space that

researcharxiv-cs-ro

GreenWAM: A World Foundation Model for Robotics

arXiv:2610.18774v1 Announce Type: new Abstract: A robot needs a world model that predicts how its actions will change the scene and a policy that chooses those actions. Models are usually built and ev

safetyarxiv-cs-ro

GReFEM: Multimodal LLMs as Zero-Shot Semantic Assistants for Physics-Guided 3D Mesh Refinement

arXiv:2607.08798v2 Announce Type: replace-cross Abstract: Adaptive volumetric finite element meshing traditionally requires iterative PDE solvers or heavily supervised, data-driven surrogates trained

local-aiarxiv-cs-cv

Grid or Nodes? Probing Object Memory in World Models Under Partial Observability

arXiv:2610.18637v1 Announce Type: cross Abstract: A robot's world model must remember objects that leave the camera's view. FloWM, a learned world model, keeps them in a spatial grid of features that

Applications

Grounding Deep Learning Framework Testing in Data Flow

arXiv:2610.15808v1 Announce Type: cross Abstract: Data flow underlies deep learning (DL) framework execution, including automatic differentiation and operator-fusion optimization. Bugs involving data

applicationsarxiv-cs-lg

Groups Don't Move as One: A Bregman Clustering View of Linearized Group Influence

arXiv:2610.14809v1 Announce Type: new Abstract: Influence functions provide an efficient alternative to retraining for assessing the effects of removing or reweighting training data. For groups, howev

Growing and Transferring Pathways for LLM Reinforcement Learning

arXiv:2610.16489v1 Announce Type: new Abstract: Reinforcement learning (RL) can substantially improve the reasoning capabilities of large language models, but an effective training run requires consid