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Generating Physically Consistent Molecules with Energy-Based Models

arXiv:2605.18381v1 Announce Type: new Abstract: Molecules in equilibrium follow a Boltzmann distribution, making the underlying energy landscape a physically grounded modeling objective. However, such

safetyarxiv-cs-lg

Tutorials

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Human DGX agent

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Generating Pretraining Tokens from Organic Data for Data-Bound Scaling

DGX agent

arXiv:2605.17849v1 Announce Type: cross Abstract: LLM pretraining is shifting from a compute-bound to a data-bound regime, where available human (organic) text falls far short of scaling demands. Howe

tutorialsarxiv-cs-ai

19 May 2026

Generating Realistic Safety-Critical Scenarios for Vehicle-Pedestrian Interactions

arXiv:2605.17229v1 Announce Type: new Abstract: Automated driving system deployment requires rigorous validation across safety-critical vehicle-pedestrian interactions, yet real-world datasets rarely

safetyarxiv-cs-ro

Generation Navigator: A State-Aware Agentic Framework for Image Generation

arXiv:2605.17969v1 Announce Type: new Abstract: Despite rapid advances in text-to-image generation, faithfully realizing user intent remains challenging, often requiring manual multi-turn trial and er

safetyarxiv-cs-cv

Generative 3D Gaussians with Learned Density Control

arXiv:2605.16355v1 Announce Type: cross Abstract: We present Density-Sampled Gaussians (DeG), a novel 3D representation designed to bridge the gap between adaptive rendering primitives and scalable ge

Tutorials

Generative Adversarial Learning from Deterministic Processes

arXiv:2605.18425v1 Announce Type: new Abstract: Physical AI is being successfully applied to data which does not follow the traditional paradigm of independent and identically distributed (i.i.d.) sam

tutorialsarxiv-cs-lg

Generative AI Advertising as a Problem of Trustworthy Commercial Intervention

arXiv:2605.18673v1 Announce Type: cross Abstract: Major deployed generative AI advertising systems preserve a visible boundary between commercial content and AI-generated responses. Yet empirical rese

agentsarxiv-cs-cl

Applications

Generative AI and the Productivity Divide: Human-AI Complementarities in Education

arXiv:2605.18143v1 Announce Type: new Abstract: Generative Artificial Intelligence (GenAI) is transforming how firms create, process, and apply knowledge, yet little is known about the heterogeneity o

applicationsarxiv-cs-ai

Generative AI and Two-Tiered Online Mental Health Communities

arXiv:2605.16279v1 Announce Type: cross Abstract: Online mental health communities (OMHCs) are tiered platforms that connect patients with licensed counselors through public Q&A forums and paid privat

Generative AI in K-12 Classrooms: A Midyear Implementation Report

arXiv:2605.16277v1 Announce Type: cross Abstract: This mid-year report summarizes teacher use of Colleague AI across 12 Washington State school districts from September 1 to December 31, 2025. Produce

Generative Artificial Intelligence for Literature Reviews

model-releasesarxiv-cs-cl

arXiv:2605.16475v1 Announce Type: cross Abstract: Generative artificial intelligence (GenAI), based on large-language models (LLMs), such as ChatGPT, has taken organizations, academia, and the public

Genflow Ad Studio: A Compound AI Architecture for Brand-Aligned, Self-Correcting Video Generation

arXiv:2605.16748v1 Announce Type: cross Abstract: Recent advancements in generative video models demonstrate high visual fidelity, yet their integration into enterprise environments is restricted by t

GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis

arXiv:2507.21035v3 Announce Type: replace Abstract: Gene expression analysis holds the key to many biomedical discoveries, yet extracting insights from raw transcriptomic data remains formidable due t

GenTS: A Comprehensive Benchmark Library for Generative Time Series Models

arXiv:2605.17804v1 Announce Type: new Abstract: Generative models have demonstrated remarkable potential in time series analysis tasks, like synthesis, forecasting, imputation, etc. However, offering

GeoFlow: Enforcing Implicit Geometric Consistency in Video Generation

arXiv:2605.18365v1 Announce Type: new Abstract: Generating geometrically consistent videos remains an open challenge: text-to-video diffusion models trained on web-scale data treat geometry only impli

GeoHand: Unlocking Prior Geometry Knowledge for Monocular 3D Hand Reconstruction

arXiv:2605.17354v1 Announce Type: new Abstract: Monocular 3D hand reconstruction is intrinsically a geometric problem, yet RGB appearance features alone often struggle to resolve severe ambiguities ca

Geometric Asymmetry in MoE Specialization: Functional Decorrelation and Representational Overlap

arXiv:2605.16349v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures achieve scalable capacity through sparse routing, yet the geometric structure of expert specialization remains po

Geometric Dictionary Learning of Dynamical Systems with Optimal Transport

arXiv:2605.18276v1 Announce Type: cross Abstract: Learning dynamical systems through operator-theoretic representations provides a powerful framework for analyzing complex dynamics, as spectral quanti

researcharxiv-cs-lg

Geometric Scaling of Bayesian Inference in LLMs

arXiv:2512.23752v5 Announce Type: replace-cross Abstract: Recent work has shown that small transformers trained in controlled 'wind-tunnel'' settings can implement exact Bayesian inference, and that t

Geometry-aware 4D Video Generation for Robot Manipulation

arXiv:2507.01099v4 Announce Type: replace-cross Abstract: Understanding and predicting dynamics of the physical world can enhance a robot's ability to plan and interact effectively in complex environm

safetyarxiv-cs-ai

Geometry-Aware Attention Guidance for Diffusion Models via Modern Hopfield Dynamics

arXiv:2603.02531v2 Announce Type: replace-cross Abstract: Classifier-Free Guidance (CFG) improves sample quality in diffusion models, but its dual-pass inference and reliance on null-condition trainin

Geometry-Aware Surrogate for Real-Time Hydrodynamics Estimation of Autonomous Ground Vehicles in Amphibious Environments

arXiv:2605.18543v1 Announce Type: new Abstract: Autonomous ground vehicles operating in shallow water or flood-prone terrains require dynamic models that account for hydrodynamic forces. However, the

agentsarxiv-cs-ro

Geometry-Aware Uncertainty Coresets for Robust Visual In-Context Learning in Histopathology

arXiv:2605.18419v1 Announce Type: cross Abstract: Vision-language models (VLMs) can couple visual perception with open-ended clinical reasoning, making them attractive for computational histopathology

Geometry-Editable and Appearance-Preserving Object Compositon

arXiv:2505.20914v2 Announce Type: replace Abstract: General object composition (GOC) aims to seamlessly integrate a target object into a background scene with desired geometric properties, while simul

Geospatial-Reasoning-Driven Vocabulary-Agnostic Remote Sensing Semantic Segmentation

arXiv:2602.08206v2 Announce Type: replace Abstract: Open-vocabulary semantic segmentation has become an important direction in remote sensing, as it enables recognition beyond predefined land-cover ca

GeoSym127K: Scalable Symbolically-verifiable Synthesis for Multimodal Geometric Reasoning

arXiv:2605.16371v1 Announce Type: cross Abstract: Large Multimodal Models (LMMs) often struggle with geometric reasoning due to visual hallucinations and a lack of mathematically precise Chain-of-Thou

GeoWorld: Geometric World Models

arXiv:2602.23058v2 Announce Type: replace Abstract: Energy-based predictive world models provide a powerful approach for multi-step visual planning by reasoning over latent energy landscapes rather th

GeoWorld-VLM: Geometry from World Models for Vision-Language Models

arXiv:2605.16713v1 Announce Type: cross Abstract: Modern Vision-Language Models (VLMs) achieve strong semantic recognition, yet remain brittle on elementary spatial relations such as left of, on, behi

safetyarxiv-cs-ai

Gesture First, LLM-Assisted Voice Complement: Exploring Multimodal Robot 'Puppeteer' Teleoperation Via Virtual Counterpart in Augmented Reality

arXiv:2506.13189v3 Announce Type: replace-cross Abstract: Robot teleoperation via augmented reality (AR) offers a promising path toward more intuitive human-robot interaction (HRI). We present a head-

researcharxiv-cs-ro

GIM: Evaluating models via tasks that integrate multiple cognitive domains

arXiv:2605.18663v1 Announce Type: new Abstract: As LLM benchmarks saturate, the evaluation community has pursued two strategies to increase difficulty: escalating knowledge demands (GPQA, HLE) or remo

GIST: Targeted Data Selection for Instruction Tuning via Coupled Optimization Geometry

arXiv:2602.18584v2 Announce Type: replace-cross Abstract: Targeted data selection has emerged as a crucial paradigm for efficient instruction tuning, aiming to identify a small yet influential subset

Global Automation Atlas

arXiv:2605.17086v1 Announce Type: cross Abstract: Automation affects the labour content of work differently across different contexts. Yet, most existing exposure measures assign fixed scores to tasks

Global Convergence of Sampling-Based Nonconvex Optimization through Diffusion-Style Smoothing

arXiv:2605.16520v1 Announce Type: new Abstract: Sampling-based optimization (SBO), like cross-entropy method and evolutionary algorithms, has achieved many successes in solving non-convex problems wit

researcharxiv-cs-lg

Local Ai

Global Prior Meets Local Consistency: Dual-Memory Augmented Vision-Language-Action Model for Efficient Robotic Manipulation

arXiv:2602.20200v2 Announce Type: replace-cross Abstract: Hierarchical Vision-Language-Action (VLA) models have rapidly become a dominant paradigm for robotic manipulation. It typically comprising a V

local-aiarxiv-cs-ai

Glocal Smoothness: Line search and adaptive step sizes can help in theory too!

arXiv:2506.12648v2 Announce Type: replace-cross Abstract: Iteration complexities for optimizing smooth functions with first-order algorithms are typically stated in terms of a global Lipschitz constan

researcharxiv-cs-lg

GLT-PEFT: Gated Lie-Tucker Parameter-Efficient Fine-Tuning for Alzheimer's Disease Diagnosis with Hippocampal Segmentation Pretraining

model-releasesarxiv-cs-cv

arXiv:2605.16769v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) has emerged as a promising paradigm for adapting pretrained models under limited data conditions. However, most e

Goal-Conditioned Supervised Learning for LLM Fine-Tuning

arXiv:2605.16345v1 Announce Type: cross Abstract: Large language models often require fine-tuning to better align their behavior with user intent at deployment. Existing approaches are commonly divide

safetyarxiv-cs-ai

Goal inference with Rao-Blackwellized Particle Filters

arXiv:2512.09269v2 Announce Type: replace Abstract: Inferring the eventual goal of a mobile agent from noisy observations of its trajectory is a fundamental estimation problem. We initiate the study o

agentsarxiv-cs-lg

Going Headless? On the Boundaries of Vertical AI Firms

arXiv:2605.17812v1 Announce Type: new Abstract: Vertical AI firms in accounting, law, healthcare, procurement, and similar domains historically bundled workflow, domain logic, and accountability into

Good flavor search in SU(5): a machine learning approach

arXiv:2511.08154v2 Announce Type: replace-cross Abstract: We revisit the fermion mass problem of the SU(5) grand unified theory using machine learning techniques. The original SU(5) model proposed by

Hardware

GPU-Accelerated Deep Learning for Heatwave Prediction and Urban Heat Risk Assessment

arXiv:2605.16435v1 Announce Type: cross Abstract: Heatwaves are an important problem in cities, and climate change makes this problem more difficult. In this paper, we present a GPU-based deep learnin

hardwarearxiv-cs-ai

GRaD-Nav++: Vision-Language Model Enabled Visual Drone Navigation with Gaussian Radiance Fields and Differentiable Dynamics

model-releasesarxiv-cs-ro

arXiv:2506.14009v2 Announce Type: replace Abstract: Autonomous drones capable of interpreting and executing high-level language instructions in unstructured environments remain a long-standing goal. Y

Gradient Dynamics of Attention: How Cross-Entropy Sculpts Bayesian Manifolds

arXiv:2512.22473v5 Announce Type: replace-cross Abstract: Transformers empirically perform precise probabilistic reasoning in carefully constructed ``Bayesian wind tunnels'' and in large-scale languag

GRAFT: Decoupling Ranking and Calibration for Survival Analysis

arXiv:2602.07884v2 Announce Type: replace-cross Abstract: Survival analysis is complicated by censored data, high-dimensional features, and non-linear interactions. Classical models offer interpretabi

Graph Embedding in the Graph Fractional Fourier Transform Domain

arXiv:2508.02383v2 Announce Type: replace Abstract: Spectral graph embedding plays a critical role in graph representation learning by generating low-dimensional vector representations from graph spec

Graph Hierarchical Recurrence for Long-Range Generalization

arXiv:2605.18387v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) and Graph Transformers (GTs) are now a fundamental paradigm for graph learning, combining the representation-learning cap

Applications

GraphMAR: Geometry-Aware Graph Learning Framework for Spatially Adaptive CT Metal Artifact Reduction

arXiv:2605.17343v1 Announce Type: new Abstract: Computed tomography (CT) metal artifact reduction (MAR) aims to reduce the severe streaking artifacts induced by metallic implants and other high-densit

applicationsarxiv-cs-cv

GraphMind: From Operational Traces to Self-Evolving Workflow Automation

arXiv:2605.17617v1 Announce Type: new Abstract: Complex operational workflows coordinating personnel, tools, and information are central to enterprise operations, yet end-to-end automation remains cha