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Fusion techniques of time frequency-based images to predict the outcome of rTMS depression therapy

arXiv:2610.00380v1 Announce Type: new Abstract: Depression is a mental condition that can lead to suicide and self-harm. Predicting the outcome of depression treatment is one of the most difficult tas

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FutureWorlds: Learning Robotic World Models from Alternative Futures

DGX agent

arXiv:2610.01019v1 Announce Type: new Abstract: Robotic world models predict action-conditioned future scenes, providing a foundation for understanding action outcomes. However, turning alternative pr

safetyarxiv-cs-cv

2 Oct 2026

G2-Nav: Grounded and Guarded Vision-Language Costmaps for Robot Social Navigation

arXiv:2607.16956v2 Announce Type: replace Abstract: Social navigation requires the robot to reason and respond in complex real-world environments. While recent works attempt to incorporate human-level

safetyarxiv-cs-ro

Gacha Decoding: Eliciting Diverse Generations Through Instruction Following

arXiv:2610.01382v1 Announce Type: new Abstract: We introduce Gacha Decoding, an inference-time method for eliciting diverse language model generations that scales with model capability. Across open-en

GenCOPE: Syn2Real Generalized Category-Level Object Pose Estimation for Robotic Picking

arXiv:2610.01758v1 Announce Type: new Abstract: Category-level object pose estimation (COPE), capable of generalizing to intra-class unknown objects, has become a core technique for robotic 3D scene u

Applications

Generalist Representation, Specialist Detection: TS-Router for Time-Series Anomaly Detection

arXiv:2610.00978v1 Announce Type: cross Abstract: Time-series anomaly detection (TSAD) is difficult to generalize across datasets because heterogeneous temporal dynamics imply different notions of nor

applicationsarxiv-cs-ai

Generalization in Neural Networks Through the Lens of Magnitude Potential

arXiv:2610.01633v1 Announce Type: new Abstract: Explaining generalization and training dynamics in neural networks remains a challenge, and various approaches have been developed to study different as

Generalization Is Stability, Not Accuracy: Multi-Axis Evaluation of LLMs

arXiv:2610.01428v1 Announce Type: cross Abstract: Generalization in large language models (LLMs) is the ability to produce consistent and semantically stable outputs when the same input is expressed i

Generalized Biomedicine Discovery

arXiv:2610.00120v1 Announce Type: new Abstract: In real-world clinical practice, medical images face open-world shifts: (i) long-tailed rare diseases, (ii) subtle lesions dominated by normal anatomy,

Generalized Design Choices for Deepfake Detectors

arXiv:2511.21507v2 Announce Type: replace Abstract: The effectiveness of deepfake detection methods often depends less on their core design and more on implementation details such as data preprocessin

Generalized Engression Models

arXiv:2610.01823v1 Announce Type: cross Abstract: We consider estimating the conditional distribution of a multivariate outcome given covariates when its coordinates may be continuous, binary, categor

Applications

Generation Provenance Before Behavior Attribution: Auditing Synthetic Speech Research Objects

arXiv:2610.01378v1 Announce Type: new Abstract: Attributing model behavior to synthetic training data requires knowing what produced each training item before estimating what that item caused. A wavef

applicationsarxiv-cs-ai

Generative Cinematographer: Composing Camera and Object Motion in 3D

arXiv:2610.02180v1 Announce Type: cross Abstract: Current controllable video generation systems often rely on 2D motion trajectories or sparse drag signals for object motion. These controls are ambigu

local-aiarxiv-cs-ai

Generative modeling of intrinsically disordered protein regions by reinforcing sparse autoencoder features

arXiv:2610.02189v1 Announce Type: new Abstract: Intrinsically disordered protein regions (IDRs) play central roles in cellular processes such as transcriptional regulation, signal transduction, and su

local-aiarxiv-cs-lg

Generative Modeling of Stochastic Dynamics for Long-Time Evolution

arXiv:2610.00546v1 Announce Type: cross Abstract: Exact stochastic equations for non-equilibrium dynamics are rarely accessible. We show that the long-time evolution of stochastic dynamics can be pred

GenGait: A Transformer-Based Model for Human Gait Anomaly Detection and Normative Twin Generation

arXiv:2604.01997v2 Announce Type: replace Abstract: Gait analysis provides an objective characterization of locomotor function and is widely used to support diagnosis and rehabilitation monitoring acr

GeoLatent: Geometry-Guided Latent Structuring with Routed Optimization for 3D Reasoning

arXiv:2610.02091v1 Announce Type: cross Abstract: Despite progress in vision-language models, 3D spatial reasoning from 2D images remains challenging. Text-based methods describe intermediate geometry

Geometric Similarity in VLM Low-Level Vision Representations

arXiv:2610.00848v1 Announce Type: cross Abstract: Vision-language models (VLMs) have emerged as powerful candidates for universal vision backbones, with representative architectures including autoregr

local-aiarxiv-cs-ai

Geometry-Aware Adaptation for Pretrained Models

arXiv:2307.12226v3 Announce Type: replace-cross Abstract: Machine learning models -- including prominent zero-shot models -- are often trained on datasets whose labels are only a small proportion of a

Geometry-Dependent Bounds for Online Non-Monotone DR-Submodular Maximization

arXiv:2610.00545v1 Announce Type: new Abstract: We study adversarial online maximization of nonnegative, non-monotone DR-submodular functions over compact convex down-closed sets. A learner commits ea

Gestalt: Large Multimodal Interplay Model

arXiv:2610.00576v1 Announce Type: new Abstract: In this paper, we propose Gestalt, a new paradigm of large multimodal model built around multimodal interplay. Despite rapid advances, large multimodal

safetyarxiv-cs-cv

Getting Out and Getting Back: World and Behavior Grounding in Real2Sim2Real Co-Training

arXiv:2610.00821v1 Announce Type: new Abstract: Simulation can expand scarce real demonstrations for co-training, yet how world fidelity and similarity to human behavior affect policy performance rema

safetyarxiv-cs-ro

GIFTBench: Diagnosing Generalization in Image Forgery Localization and Informing Model Design

arXiv:2610.01778v1 Announce Type: new Abstract: Reliable evaluation of image forgery localization (IFL) requires assessing models under diverse distribution changes, yet existing benchmarks often cove

Applications

GlassGuard: Verified Glass Plane Mapping for Robot Navigation

arXiv:2610.02110v1 Announce Type: new Abstract: Transparent and specular surfaces pose a serious challenge to LiDAR-based SLAM and navigation because laser returns may pass through glass, leaving coll

applicationsarxiv-cs-ro

Global Coherence: When Every Agent Is Right and the Team Is Still Wrong - A Local-to-Global Semantic Foundation for Multi-Agent Collaboration

arXiv:2610.02036v1 Announce Type: new Abstract: AI agents can each make locally valid decisions yet jointly produce an invalid result. We call this the global coherence problem: a failure of shared st

GLoC-EHR: Evidence-Cited Clinical Reasoning over Global Context and Local EHR Events

arXiv:2610.01076v1 Announce Type: new Abstract: Structured electronic health records (EHRs) contain a patient's clinical trajectory as a sequence of clinical codes. Answering clinical questions from s

local-aiarxiv-cs-lg

GPEC: Efficient Pre-LLM Gaussian Process Embedding Correction for Cardiac Video Caption Generation

arXiv:2610.00196v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have shown strong potential for video understanding and caption generation, but their performance may decline i

Gradient-Aligned Pair Selection for Personalized Preference Optimization

arXiv:2610.00061v1 Announce Type: new Abstract: Personalizing large language models (LLMs) requires aligning generation behavior with user-specific preferences rather than aggregate quality. While Dir

Grand Canonical Generators

arXiv:2610.00683v1 Announce Type: new Abstract: We introduce Grand Canonical Generators (GCG), a generative framework that extends Boltzmann generators to the grand canonical ensemble. We present two

Graph Representation via Elements of Discrete Morse and Cobordism Theories

arXiv:2610.01937v1 Announce Type: new Abstract: Topology is, by its nature and design, suited to structure that is nonlinear, multiscale, and nonstationary - however, within machine learning, its use

Greed Is Learned: Visible Incentives as Reward-Hacking Triggers

arXiv:2606.16914v2 Announce Type: replace Abstract: Safety evaluations test a policy on prompts that omit the incentive information deployment supplies: a commission, a performance score, a dashboard

Groundability, Not Scale Alone: When Weak Reviewers Can Audit Strong Coding Agents

arXiv:2610.01023v1 Announce Type: cross Abstract: Coding agents can return plausible patches that omit required behavior. These failures are hard to review because long traces and confident summaries

Grounding Large Language Models in DSGE Simulators for Policy Generation and Forecasting

arXiv:2610.01128v1 Announce Type: new Abstract: Large language models can produce economic policy responses that sound reasonable, but this does not show that their actions are consistent with economi

Tutorials

Group-Invariant Statistics Determine Embedding Geometry: Harmonic Analysis of Representations from Bach to the Night Sky

arXiv:2610.00647v1 Announce Type: new Abstract: The representations that language models learn for concepts such as months, weekdays, and places display consistent geometric structure: circles and sad

tutorialsarxiv-cs-lg

GS-PQM: A Parameter-Domain Quality Metric for Compressed Gaussian Splatting

arXiv:2610.00195v1 Announce Type: cross Abstract: Recent advances in Gaussian Splatting (GS) compression have enabled substantial reductions in GS model size. Reliable objective quality assessment is

GUI-HARVEST: Self-Improving GUI Agents through Evidence-Driven Harness Evolution

arXiv:2610.00948v1 Announce Type: cross Abstract: The executable harness surrounding a GUI model determines how observations are assembled, actions are executed, and verification, recovery, and termin

Gumbel Straight Flow: Distilling Autoregressive Models into One-step Flow Maps

arXiv:2610.00497v1 Announce Type: cross Abstract: We present Gumbel Straight Flow (GSF), a continuous flow map language model that leverages the noise-data coupling of a pretrained autoregressive lang

Agents

H-SPAR: Hydrodynamic-aware Simulation for Particle Transport and Autonomous Robots

arXiv:2610.01985v1 Announce Type: new Abstract: Environmental robotic sampling requires considering the dual influence of water currents on robotic motion and particle transport. Existing marine robot

agentsarxiv-cs-ro

HADRec: A Hierarchy-Aware Drug Recommendation Framework by Fusing Molecular Knowledge and Electronic Health Record

arXiv:2610.00984v1 Announce Type: new Abstract: Accurate medication recommendation is central to clinical decision-making, directly determining therapeutic efficacy and patient safety. However, existi

Hardening Soft Information: Evidence on Analyst Integration Costs

arXiv:2505.12269v4 Announce Type: replace-cross Abstract: We examine how the cost of transforming qualitative information into precise numerical estimates--a form of integration cost--creates a struct

Hardware-Algorithm Co-Optimization of Early-Exit Neural Networks for Multi-Core Edge Accelerators

arXiv:2512.04705v3 Announce Type: replace-cross Abstract: The deployment of Early-Exiting Neural Networks (EENNs) on edge accelerators requires optimizing not only the network architecture but also it

researcharxiv-cs-cv

Harnessing Domain Specialists in Multimodal Mixture-of-Experts for Efficient Adaptation

arXiv:2610.02123v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures scale model capacity through sparse computation, routing each token through only a small subset of experts. In th

researcharxiv-cs-cv

Harnessing Vision-Language Models for Perceptual Quality Assessment and Autonomous Content Adjustment in Augmented Reality

arXiv:2610.00677v1 Announce Type: new Abstract: Advancements in augmented reality (AR) continue to foster innovative solutions, facilitating novel methodologies within educational systems, healthcare

Have an LLM Write Your Anomaly Detector: Autonomous Discovery of Compact, Interpretable Detectors for Time Series

arXiv:2610.01223v1 Announce Type: cross Abstract: Time-series anomaly detection trades off predictive accuracy, computational efficiency, and interpretability. We use a large language model not as the

Tutorials

HAWK: Rethinking Multimodal Drafting for Speculative Decoding

arXiv:2610.00623v1 Announce Type: new Abstract: Speculative decoding has achieved substantial lossless speedups for LLMs, but remains less effective for large vision-language models (LVLMs), where lig

tutorialsarxiv-cs-cv

Heavy-Tailed Memory Traces in Long-Horizon Language Agents

arXiv:2610.00010v1 Announce Type: new Abstract: Long-horizon language agents increasingly rely on external memory as a frozen world model, yet current memory systems are usually judged only by task su

Heteroskedastic Canonical Polyadic Tensor Decomposition

arXiv:2610.00498v1 Announce Type: cross Abstract: When minimizing the squared-error loss, the popular CP decomposition can be interpreted as parameter inference in a Gaussian model with a low-rank mea

HHR: Hierarchical Hash Retrieval for Efficient LLM Generation

arXiv:2610.01230v1 Announce Type: new Abstract: Efficient long-context inference is essential for large language models (LLMs), yet it poses a severe computational bottleneck. Hash-based retrieval off