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GenCellAgent: Generalizable, Training-Free Cellular Image Segmentation via Large Language Model Agents

arXiv:2510.13896v2 Announce Type: replace-cross Abstract: Cellular image segmentation is essential for quantitative biology yet remains difficult due to heterogeneous modalities, morphological variabi

agentsarxiv-cs-ai

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Gender Fairness in Audio Deepfake Detection: Performance and Disparity Analysis

DGX agent

arXiv:2603.09007v2 Announce Type: replace-cross Abstract: Audio deepfake detection aims to detect real human voices from those generated by Artificial Intelligence (AI) and has emerged as a significan

safetyarxiv-cs-ai

12 May 2026

General Agent Evaluation

arXiv:2602.22953v2 Announce Type: replace Abstract: General-purpose agents perform tasks in unfamiliar environments without domain-specific manual customization. Yet no study has systematically measur

Generalization Bounds of Emergent Communications for Agentic AI Networking

arXiv:2605.08613v1 Announce Type: new Abstract: The evolution of 6G networking toward agentic AI networking (AgentNet) systems requires a shift from traditional data pipelines to task-aware, agentic A

agentsarxiv-cs-ai

Local Ai

Generalization Error Bounds for Picard-Type Operator Learning in Nonlinear Parabolic PDEs

arXiv:2605.10277v1 Announce Type: new Abstract: Operator learning for partial differential equations (PDEs) aims to learn solution operators on infinite-dimensional function spaces from finite-resolut

local-aiarxiv-cs-lg

Generalized Category Discovery in Federated Graph Learning

arXiv:2605.08178v1 Announce Type: cross Abstract: Federated Graph Learning (FGL) enables collaborative learning over distributed graph data, yet existing approaches largely rely on a closed-world assu

Local Ai

Generalized Hierarchical Bayesian Segmentation with Irregular Designs, Multi-Sequence Hierarchies, and Grouped/Latent-Group Designs

arXiv:2603.14681v2 Announce Type: replace Abstract: Bayesian change-point and segmentation models provide uncertainty-aware piecewise-constant representations of ordered data, but exact inference is o

local-aiarxiv-cs-lg

Generalized Wasserstein Flow Matching: Transport Plans, Everywhere, All at Once

arXiv:2605.08424v1 Announce Type: new Abstract: Flow matching has recently emerged as a flexible and efficient framework for generative modelling by learning deterministic transport dynamics between p

researcharxiv-cs-lg

Generating Leakage-Free Benchmarks for Robust RAG Evaluation

arXiv:2605.08838v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) is widely used to augment large language models (LLMs) with external knowledge. However, many benchmark datasets,

Generating Symmetric Materials using Latent Flow Matching

arXiv:2605.10115v1 Announce Type: new Abstract: Tackling the task of materials generation, we aim to enhance the previously proposed All-atom Diffusion Transformer (ADiT) by introducing SymADiT, a sym

Generating synthetic electronic health record data using agent-based models to evaluate machine learning robustness under mass casualty incidents

arXiv:2605.09951v1 Announce Type: new Abstract: ML models in healthcare are typically evaluated using curated real-world EHR data. A key limitation of such evaluations is that they may fail to assess

agentsarxiv-cs-lg

Generative Actor-Critic with Soft Bridge Policies

arXiv:2605.08733v1 Announce Type: new Abstract: Expressive generative policies such as diffusion and flow models are appealing for MaxEnt online reinforcement learning because of their ability to mode

Generative Adversarial Post-Training Mitigates Reward Hacking in Live Human-AI Music Interaction

arXiv:2511.17879v4 Announce Type: replace Abstract: Most applications of generative AI involve a sequential interaction in which a person inputs a prompt and waits for a response, and where reaction t

safetyarxiv-cs-lg

Generative AI Fuels Solo Entrepreneurship, but Teams Still Lead at the Top

arXiv:2605.10291v1 Announce Type: cross Abstract: Recent advances in generative artificial intelligence (AI) are reshaping who enters entrepreneurship, but not who reaches the top of the quality distr

Tutorials

Generative Experiences for Digital Mental Health Interventions: Evidence from a Randomized Study

arXiv:2604.07558v2 Announce Type: replace-cross Abstract: Digital mental health (DMH) tools have extensively explored personalization of interventions to users' needs and contexts. However, this perso

tutorialsarxiv-cs-ai

Generative Giants, Retrieval Weaklings: Why do Multimodal Large Language Models Fail at Multimodal Retrieval?

arXiv:2512.19115v2 Announce Type: replace Abstract: Despite the remarkable success of multimodal large language models (MLLMs) in generative tasks, we observe that they exhibit a counterintuitive defi

GenMed: A Pairwise Generative Reformulation of Medical Diagnostic Tasks

model-releasesarxiv-cs-cv

arXiv:2605.10645v1 Announce Type: new Abstract: Data-driven medical AI is traditionally formulated as a discriminative mapping from input X to output Y via a learned function f, which does not general

Hardware

Geometric 4D Stitching for Grounded 4D Generation

arXiv:2605.09984v1 Announce Type: cross Abstract: Recent 4D generation methods complete scene-level missing information using generative models and reconstruct the scene into radiance-based representa

hardwarearxiv-cs-ai

Geometric Flood Depth Estimation: Fusing Transformer-Based Segmentation with Digital Elevation Models

arXiv:2605.08521v1 Announce Type: new Abstract: Post-disaster situational awareness relies heavily on understanding both the extent and the volume of floodwaters. While 2D semantic segmentation provid

Hardware

Geometrically Approximated Modeling for Emitter-Centric Ray-Triangle Filtering in Arbitrarily Dynamic LiDAR Simulation

arXiv:2605.10457v1 Announce Type: cross Abstract: Real-time Light Detection And Ranging (LiDAR) simulation must find, per emitted ray, the closest intersecting triangle even in dynamic scenes containi

hardwarearxiv-cs-ro

Geometrically Constrained Stenosis Editing in Coronary Angiography via Entropic Optimal Transport

arXiv:2605.08851v1 Announce Type: cross Abstract: The scarcity of high-quality imaging data for coronary angiography (CAG) stenosis limits the clinical translation of automated stenosis detection. Syn

Geometry-Aware Discretization Error of Diffusion Models

arXiv:2605.08392v1 Announce Type: new Abstract: Practical diffusion sampling is a numerical approximation problem: under a fixed inference budget, one must simulate a reverse-time ODE or SDE using onl

Geometry-aware Prototype Learning for Cross-domain Few-shot Medical Image Segmentation

arXiv:2605.10885v1 Announce Type: new Abstract: Cross-domain few-shot medical image segmentation (CD-FSMIS) requires a model to generalise simultaneously to novel anatomical categories and unseen imag

Geometry Conflict: Explaining and Controlling Forgetting in LLM Continual Post-Training

arXiv:2605.09608v1 Announce Type: new Abstract: Continual post-training aims to extend large language models (LLMs) with new knowledge, skills, and behaviors, yet it remains unclear when sequential up

Geometry-free prediction of inertial lift forces in microfluidic devices using deep learning

arXiv:2605.08109v1 Announce Type: new Abstract: Inertial microfluidic devices (IMDs) offer low-cost, high-throughput alternative techniques for many traditional particle- (or cell-) manipulation tasks

Geometry Guided Self-Consistency for Physical AI

arXiv:2605.08638v1 Announce Type: cross Abstract: State-of-the-art physical AI models generate a chunk of actions per inference through diffusion or flow matching, iteratively refining an initial nois

Geospatial-Temporal Sensemaking of Remote Sensing Activity Detections with Multimodal Large Language Model

arXiv:2605.10739v1 Announce Type: cross Abstract: We introduce SMART-HC-VQA, a Sentinel-2-based visual question answering dataset derived from the IARPA SMART Heavy Construction dataset, designed for

Tutorials

GESR: A Genetic Programming-Based Symbolic Regression Method with Gene Editing

arXiv:2605.10685v1 Announce Type: new Abstract: Mathematical formulas serve as a language through which humans communicate with nature. Discovering mathematical laws from scientific data to describe n

tutorialsarxiv-cs-ai

GIFT: Guided Importance-Aware Fine-Tuning for Diffusion Language Models

model-releasesarxiv-cs-cl

arXiv:2509.20863v3 Announce Type: replace Abstract: Diffusion models have recently shown strong potential in language modeling, offering faster generation compared to traditional autoregressive approa

GLAI: GreenLightningAI for Accelerated Training through Knowledge Decoupling

arXiv:2510.00883v2 Announce Type: replace-cross Abstract: In this work we introduce GreenLightningAI (GLAI), a new architectural block designed as an alternative to conventional MLPs. The central idea

GLEAM: A Multimodal Imaging Dataset and HAMM for Glaucoma Classification

arXiv:2603.12800v2 Announce Type: replace-cross Abstract: We propose glaucoma lesion evaluation and analysis with multimodal imaging (GLEAM), the first publicly available tri-modal glaucoma dataset co

GLiNER-Relex: A Unified Framework for Joint Named Entity Recognition and Relation Extraction

model-releasesarxiv-cs-cl

arXiv:2605.10108v1 Announce Type: new Abstract: Joint named entity recognition (NER) and relation extraction (RE) is a fundamental task in natural language processing for constructing knowledge graphs

GLiNER2-PII: A Multilingual Model for Personally Identifiable Information Extraction

arXiv:2605.09973v1 Announce Type: cross Abstract: Reliable detection of personally identifiable information (PII) is increasingly important across modern data-processing systems, yet the task remains

Global Optimization via Softmin Energy Minimization

arXiv:2509.17815v2 Announce Type: replace Abstract: Global optimization, particularly for non-convex functions with multiple local minima, poses significant challenges for traditional gradient-based m

GNN for Structural Displacement Prediction

arXiv:2605.08303v1 Announce Type: cross Abstract: Accurate prediction of structural displacements under external loading is fundamental to structural health monitoring and seismic safety assessment. A

GONE: Structural Knowledge Unlearning via Neighborhood-Expanded Distribution Shaping

arXiv:2603.12275v1 Announce Type: cross Abstract: Unlearning knowledge is a pressing and challenging task in Large Language Models (LLMs) because of their unprecedented capability to memorize and dige

Governed Metaprogramming for Intelligent Systems: Reclassifying Eval as a Governed Effect

arXiv:2605.05248v2 Announce Type: replace-cross Abstract: AI systems increasingly synthesize executable structure at runtime: LLMs generate programs, agents construct workflows,self-improving systems

Governing AI-Assisted Security Operations: A Design Science Framework for Operational Decision Support

arXiv:2605.09534v1 Announce Type: cross Abstract: Engineering managers increasingly must decide how to introduce generative artificial intelligence (AI), retrieval-augmented generation, and coding age

Hardware

GPU-Accelerated Synthesis of Mixed-Boolean Arithmetic: Beyond Caching

arXiv:2605.08243v1 Announce Type: cross Abstract: Synthesizing Mixed-Boolean Arithmetic (MBA) expressions from input-output examples is central to program deobfuscation and also useful for compiler op

hardwarearxiv-cs-lg

Graph Computation Meets Circuit Algebra: A Task-Aligned Analysis of Graph Neural Networks for Electronic Design Automation

arXiv:2605.08291v1 Announce Type: cross Abstract: EDA problems are graph-structured, but not all graph-structured problems call for the same GNN computation. We argue that successful GNN-for-EDA metho

GraphBench: Next-generation graph learning benchmarking

arXiv:2512.04475v5 Announce Type: replace-cross Abstract: Machine learning on graphs has made substantial progress across domains such as molecular property prediction and chip design. Yet benchmarkin

GravityGraphSAGE: Link Prediction in Directed Attributed Graphs

arXiv:2605.09408v1 Announce Type: new Abstract: Link prediction (inferring missing or future connections between nodes in a graph) is a fundamental problem in network science with widespread applicati

GRC: Unifying Reasoning-Driven Generation, Retrieval and Compression

arXiv:2605.09100v1 Announce Type: new Abstract: Text embedding and generative tasks are usually trained separately based on large language models (LLMs) nowadays. This causes a large amount of trainin

agentsarxiv-cs-cl

GridProbe: Posterior-Probing for Adaptive Test-Time Compute in Long-Video VLMs

arXiv:2605.10762v1 Announce Type: cross Abstract: Long-video understanding in VLMs is bottlenecked by a single monolithic forward pass over thousands of frames at quadratic attention cost. A common mi

GRIT: Teaching MLLMs to Think with Images

arXiv:2505.15879v2 Announce Type: replace-cross Abstract: Recent studies have demonstrated the efficacy of using Reinforcement Learning (RL) in building reasoning models that articulate chains of thou

Grounded or Guessing? LVLM Confidence Estimation via Blind-Image Contrastive Ranking

model-releasesarxiv-cs-cl

arXiv:2605.10893v1 Announce Type: new Abstract: Large vision-language models suffer from visual ungroundedness: they can produce a fluent, confident, and even correct response driven entirely by langu

Grounded Satirical Generation with RAG

arXiv:2605.10853v1 Announce Type: new Abstract: Humor generation remains challenging task for Large Language Models (LLMs), due to their subjective nature. We focus on satire, a form of humor strongly

researcharxiv-cs-cl

Grounding the Score: Explicit Visual Premise Verification for Reliable Vision-Language Process Reward Models

arXiv:2603.16253v2 Announce Type: replace-cross Abstract: Vision-language process reward models (VL-PRMs) are increasingly used to score intermediate reasoning steps and rerank candidates under test-t