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GEESE: Genotype-aware End-to-End Spatio-temporal Embedding for Behavioral Phenotyping

arXiv:2605.24370v1 Announce Type: new Abstract: Behavioral phenotyping of genetic animal models currently requires labor-intensive manual feature engineering that limits reproducibility and scalabilit

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GeMPO: Generalized Measure Matching for Online Diffusion Reinforcement Learning

DGX agent

arXiv:2603.10250v2 Announce Type: replace Abstract: A commonly used family of RL algorithms for diffusion policies conducts softmax reweighting over samples from the behavior policy, which often induc

safetyarxiv-cs-lg

26 May 2026

Generalizable Vision-Language Few-Shot Adaptation with Predictive Prompts and Negative Learning

arXiv:2505.11758v2 Announce Type: replace-cross Abstract: Few-shot adaptation of vision-language models remains fundamentally limited by how negative class signals are handled at inference. Existing m

Generalized Evidential Deep Learning: From a Bayesian Perspective

arXiv:2605.25599v1 Announce Type: new Abstract: Evidential Deep Learning (EDL) has emerged as an efficient, sampling-free strategy for uncertainty estimation. A series of EDL variants have been propos

Generating 3D models from sketches of human faces using a combined approach of Convolutional Neural Networks, Procedural Modeling, and Contour Mapping

arXiv:2605.25418v1 Announce Type: cross Abstract: Generating 3D models from face sketches is an active topic of research in Computer Graphics due to its potential to tremendously facilitate the modeli

Applications

Generating Legal Commentaries from Case Databases via Retrieval, Clustering, and Generation

arXiv:2605.24534v1 Announce Type: new Abstract: We present a fully automated pipeline that transforms large collections of court decisions into legal commentaries for statutes - without providing any

applicationsarxiv-cs-cl

Generation Enhances Understanding in Unified Multimodal Models via Multi-Representation Generation

arXiv:2601.21406v3 Announce Type: replace-cross Abstract: Unified Multimodal Models (UMMs) integrate both visual understanding and generation within a single framework. Their ultimate aspiration is to

Generative AI impacts on intra-urban inequality and skill premium in Beijing

arXiv:2605.25505v1 Announce Type: cross Abstract: Generative artificial intelligence (GenAI) is the first automation wave to reach high-cognitive tasks at scale, yet its effects on intra-urban inequal

Generative modeling of granular flow on inclined planes using conditional flow matching

arXiv:2604.04453v2 Announce Type: replace-cross Abstract: Granular flows govern many natural and industrial processes, yet their interior kinematics and mechanics remain largely unobservable, as exper

Generative Neural Operators through Diffusion Last Layer

arXiv:2602.04139v2 Announce Type: replace Abstract: Neural operators provide a powerful framework for learning discretization invariant mappings between function spaces, but standard deterministic mod

Generative OOD-regularized Model-based Policy Optimization

arXiv:2605.24405v1 Announce Type: cross Abstract: We study sequential decision-making with offline reinforcement learning (RL). Traditional offline RL policies may result in out-of-distribution (OOD)

Local Ai

Generative Representation Learning on Hyper-relational Knowledge Graphs via Masked Discrete Diffusion

arXiv:2605.24064v1 Announce Type: cross Abstract: Hyper-relational knowledge graphs (HKGs) effectively represent complex facts. While inferring new knowledge in HKGs is a critical problem, current met

local-aiarxiv-cs-ai

Generative Visual Code Mobile World Models

arXiv:2602.01576v2 Announce Type: replace-cross Abstract: Mobile Graphical User Interface (GUI) World Models (WMs) offer a promising path for improving mobile GUI agent performance at train- and infer

Geo-Expert: Towards Expert-Level Geological Reasoning via Parameter-Efficient Fine-Tuning

arXiv:2605.24844v1 Announce Type: new Abstract: While general-purpose Large Language Models (LLMs) applied to Geology often hallucinate when reasoning about subsurface structures and deep-time evoluti

GeoMathCode: Understanding Interleaved Math-Code Reasoning for Geometry Problem Solving

arXiv:2605.25384v1 Announce Type: new Abstract: Mathematical reasoning is a hallmark of human intelligence, requiring logical deduction, symbolic manipulation, and abstract thinking. Recent multimodal

researcharxiv-cs-cl

Geometric Evolution Maps: Extracting Stable Concept Probes from Transformer Residual Streams

arXiv:2605.25848v1 Announce Type: cross Abstract: Concept probes extracted from transformer residual streams are only as reliable as the layer from which they are extracted. The common practice of pro

Geometric Flow Matching for Molecular Conformation Generation via Manifold Decomposition

arXiv:2605.25577v1 Announce Type: cross Abstract: The generation of accurate 3D molecular conformations is a pivotal challenge in computational chemistry and drug discovery. Recently, diffusion and fl

Geometric Workspace Analysis and Transmission-Aware Dynamics of a Serial Spherical Tool for Microsurgery

arXiv:2605.24760v1 Announce Type: new Abstract: We present a kinematic and transmission-aware design framework for a serial spherical mechanism with an additional translational degree of freedom for m

researcharxiv-cs-ro

Local Ai

Geometry Adaptive Counterfactual Distribution Learning with Diffusion-Guided Smoothing

arXiv:2605.25811v1 Announce Type: cross Abstract: We study counterfactual distribution learning for high-dimensional outcomes whose counterfactual law may concentrate near lower-dimensional structure.

local-aiarxiv-cs-lg

GeoSVG-RL: Geometry-Aware Reinforcement Learning for Layout-Constrained Text-to-SVG Diagram Generation

arXiv:2605.25447v1 Announce Type: new Abstract: Generating structured, editable diagrams remains a significant challenge for contemporary large language models, despite their proficiency in general-pu

safetyarxiv-cs-cl

GIBLy: Improving 3D Semantic Segmentation through an Architecture-Agnostic Lightweight Geometric Inductive Bias Layer

arXiv:2605.24243v1 Announce Type: cross Abstract: In 3D scene understanding, deep learning models rely on large models and extensive training to capture basic geometric structures that are present in

GL-LFGNN:A Global-Local Dual-branch Causal Graph Neural Network Based on Liang-Kleeman Information Flow for EEG Emotion Recognition

arXiv:2605.25061v1 Announce Type: cross Abstract: EEG-based emotion recognition holds significant promise for objective diagnosis of mood disorders. Graph neural networks (GNNs) have emerged as the do

Global Convergence of Wasserstein Policy Gradient for Entropy-Regularized Reinforcement Learning

arXiv:2605.26078v1 Announce Type: new Abstract: Wasserstein policy gradient (WPG) is a policy optimization method for reinforcement learning (RL) that exploits the optimal-transport geometry of action

safetyarxiv-cs-lg

Global linear convergence of entropy-regularized softmax policy gradient beyond tabular MDPs

arXiv:2605.24939v1 Announce Type: new Abstract: We study the global convergence of policy gradient for infinite-horizon entropy-regularized Markov decision processes (MDPs) with continuous state and a

safetyarxiv-cs-lg

Applications

Global Sequential Testing for Multi-Stream Auditing

arXiv:2602.21479v2 Announce Type: replace-cross Abstract: Across many risk-sensitive areas, it is critical to continuously audit machine learning systems as we receive more data to quickly determine i

applicationsarxiv-cs-lg

GlobalDentBench: A Multinational Benchmark for Evaluating LLM Clinical Reasoning in Dentistry with Expert Calibration

arXiv:2605.24636v1 Announce Type: new Abstract: While large language models (LLMs) hold transformative potential for medicine, their reasoning robustness and safety in real-world clinical scenarios re

Go witheFlow: Real-time Emotion Driven Audio Effects Modulation

arXiv:2510.02171v3 Announce Type: replace-cross Abstract: Music performance is a distinctly human activity, intrinsically linked to the performer's ability to convey, evoke, or express emotion. Machin

Goal-driven Bayesian Optimal Experimental Design for Robust Decision-Making Under Model Uncertainty

model-releasesarxiv-cs-lg

arXiv:2605.26093v1 Announce Type: new Abstract: Bayesian optimal experimental design (BOED) selects experiments to maximize information gain about model parameters. However, in decision-critical setti

Agents

GRAIL: AI translation for scientists application workflow on satellite data

arXiv:2605.24784v1 Announce Type: new Abstract: Domain scientists increasingly develop Python scripts to analyze satellite imagery but they lack scalability to large-scale data. This paper demonstrate

agentsarxiv-cs-ai

Grammatically-Guided Sparse Attention for Efficient and Interpretable Transformers

arXiv:2605.24518v1 Announce Type: cross Abstract: The quadratic complexity of self-attention in Transformer models remains a significant bottleneck for processing long sequences and deploying large la

GreenSeg: Ground Segmentation Algorithm for Agricultural Robots in Mediterranean Greenhouses using RGB-D Point Clouds

model-releasesarxiv-cs-ro

arXiv:2605.25279v1 Announce Type: new Abstract: Greenhouse agriculture in the Mediterranean region faces significant automation challenges due to its unique structural and environmental constraints. T

GroupTravelBench: Benchmarking LLM Agents on Multi-Person Travel Planning

model-releasesarxiv-cs-cl

arXiv:2605.25200v1 Announce Type: new Abstract: Travel planning is a realistic task for evaluating the planning and tool-use abilities of LLM agents. However, existing benchmarks typically assume only

Grouter: Decoupling Routing from Representation for Accelerated MoE Training

arXiv:2603.06626v2 Announce Type: replace-cross Abstract: Traditional Mixture-of-Experts (MoE) training typically proceeds without any structural priors, effectively requiring the model to simultaneou

Grow-Prune-Freeze Networks: Adaptive & Continual Learning Technique for Olfactory Navigation

arXiv:2605.25170v1 Announce Type: cross Abstract: Training data for olfaction is scattered through disparate, non-standardized datasets that limit the ability to build representative world models. Olf

Growing a Neural Network in Breadth, Depth, and Time

arXiv:2605.25174v1 Announce Type: cross Abstract: Spatial and temporal resource constraints are critical for both biological and artificial intelligent systems. Here we define differentiable cost term

Guaranteeing Conservation of Integrals with Projection in Physics-Informed Neural Networks

arXiv:2511.09048v2 Announce Type: replace Abstract: We propose a novel projection method that guarantees the conservation of integral quantities in Physics-Informed Neural Networks (PINNs). While the

Guarded Repair for Harm-Aware Post-hoc Replacement of LLM Mathematical Reasoning

arXiv:2605.24613v1 Announce Type: cross Abstract: Post-hoc repair of LLM mathematical reasoning introduces an asymmetric risk: fixing an incorrect reasoning trace is useful, but replacing a trace that

Guess the Unified Model: How Much Can We Recover from Generated Images?

arXiv:2605.25254v1 Announce Type: cross Abstract: With unified model-generated images now widespread online, attributing their model of origin offers a path toward transparency and deeper insight into

Guided Flow Matching for Forward and Inverse PDE Problems with Sparse Observations: Algorithm and Theory

model-releasesarxiv-cs-lg

arXiv:2605.25509v1 Announce Type: cross Abstract: Reconstructing PDE solutions from sparse observations is a core challenge in scientific computing. We present FM4PDE, a flow-matching generative frame

Hardware

H^{2}MT: Semantic Hierarchy-Aware Hierarchical Memory Transformer

arXiv:2605.24930v1 Announce Type: new Abstract: Transformer-based LLMs achieve strong results on many language tasks; however, long inputs remain challenging because context windows are finite, and pr

hardwarearxiv-cs-cl

Hadamard Representation: Scaffolding Performance Across Model-free RL

model-releasesarxiv-cs-lg

arXiv:2406.09079v5 Announce Type: replace Abstract: Deep reinforcement learning agents progressively lose representational capacity during training: neurons become dormant, removing active capacity fr

Hardware-Aware Federated Learning for Speech Emotion Recognition

arXiv:2605.24712v1 Announce Type: new Abstract: Federated learning (FL) enables privacy-preserving collaborative training across distributed edge devices, but real deployments involve heterogeneous cl

Harmony in Diversity: Multi-domain Contrastive Policy Optimization for Large Reasoning Models

arXiv:2605.25443v1 Announce Type: new Abstract: Post-training has significantly enhanced the reasoning capability of Large Reasoning Models (LRMs), especially with Reinforcement Learning (RL) like Gro

safetyarxiv-cs-cl

Agents

Harnessing AtomisticSkills for Agentic Atomistic Research

arXiv:2605.24002v1 Announce Type: cross Abstract: Computational materials science and chemistry span vast knowledge domains and fractured software ecosystems. Although large language models (LLMs) hav

agentsarxiv-cs-ai

HEAPr: Hessian-based Efficient Atomic Expert Pruning in Output Space

arXiv:2509.22299v3 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) architectures in large language models (LLMs) deliver exceptional performance and reduced inference costs compared to

HeartBeatAI: An Interpretable and Robust Deep Learning Framework for Multi-Label ECG Arrhythmia Detection

arXiv:2605.24588v1 Announce Type: new Abstract: While Deep Learning (DL) enhances automated electrocardiogram (ECG) analysis, clinical deployment is hindered by class imbalance and the generalization

Applications

HeLoM: Hierarchical Learning for Whole-Body Loco-Manipulation by a Hexapod Robot

arXiv:2509.23651v3 Announce Type: replace Abstract: In nature, animals often need to move/manipulate objects comparable in weight/size to their own bodies. Compared to grasping and carrying, pushing p

applicationsarxiv-cs-ro

Local Ai

Hera: Learning Long-Horizon Coordination for Device-Cloud Collaborative LLM Agents

arXiv:2605.24598v1 Announce Type: new Abstract: Large language model (LLM) agents excel at solving complex long-horizon tasks through autonomous interaction with environments. However, their real-worl

local-aiarxiv-cs-ai