All entries

FrequencyCT: Frequency domain pseudo-label generation for self-supervised low-dose CT denoising

arXiv:2605.10583v1 Announce Type: new Abstract: Despite extensive research on computed tomography (CT) denoising, few studies exploit projection-domain data characteristics to mitigate noise correlati

applicationsarxiv-cs-cv

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Frictional Q-Learning

DGX agent

arXiv:2509.19771v5 Announce Type: replace-cross Abstract: Off-policy reinforcement learning suffers from extrapolation errors when a learned policy selects actions that are weakly supported in the rep

safetyarxiv-cs-ai

12 May 2026

From a pure 'do good for the world' mission perspective, having the acting like a solid personalized tutor is one of the better uses of AI. …

applicationsethan-mollick--x

From a pure 'do good for the world' mission perspective, having the acting like a solid personalized tutor is one of the better uses of AI. If OpenAI cares about the mission of making the world a bett

From Articulated Kinematics to Routed Visual Control for Action-Conditioned Surgical Video Generation

model-releasesarxiv-cs-cv

arXiv:2605.08712v1 Announce Type: new Abstract: Action-conditioned surgical video generation is a critical yet highly challenging problem for robotic surgery. The core difficulty is that low-dimension

From Controlled to the Wild: Evaluation of Pentesting Agents for the Real-World

arXiv:2605.10834v1 Announce Type: new Abstract: AI pentesting agents are increasingly credible as offensive security systems, but current benchmarks still provide limited guidance on which will perfor

applicationsarxiv-cs-ai

From Detection to Recovery: Operational Analysis on LLM Pre-training with 504 GPUs

arXiv:2605.09370v1 Announce Type: cross Abstract: Large-scale AI training is now fundamentally a distributed systems problem, and hardware failures have become routine operating conditions rather than

local-aiarxiv-cs-ai

From Historical Tabular Image to Knowledge Graphs: A Provenance-Aware Modular Pipeline

arXiv:2605.08222v1 Announce Type: cross Abstract: Handwritten archival tables contain rich historical information, yet transforming them into structured representations, such as Knowledge Graphs, requ

applicationsarxiv-cs-ai

From Holo Pockets to Electron Density: GPT-style Drug Design with Density

arXiv:2605.08767v1 Announce Type: new Abstract: Recent advances in generative modeling have enabled significant progress in structure-based drug design (SBDD). Existing methods typically condition mol

From Mechanistic to Compositional Interpretability

arXiv:2605.08934v1 Announce Type: new Abstract: Mechanistic interpretability aims to explain neural model behaviour by reverse-engineering learned computational structure into human-understandable com

researcharxiv-cs-lg

From Ontology Conformance to Admissible Reconfiguration: A RoSO/SMGI Adequacy Argument for Robotic Service Governance

arXiv:2605.08185v1 Announce Type: cross Abstract: The Robotic Service Ontology (RoSO) gives service robotics a typed semantic vocabulary for services, functions, interactions, and deployment-sensitive

From Passive Reuse to Active Reasoning: Grounding Large Language Models for Neuro-Symbolic Experience Replay

arXiv:2605.09419v1 Announce Type: new Abstract: While experience replay is essential for data efficiency in reinforcement learning (RL), standard methods treat the replay buffer as a passive memory sy

From Pixels to Concepts: Do Segmentation Models Understand What They Segment?

model-releasesarxiv-cs-cv

arXiv:2605.09591v1 Announce Type: new Abstract: Segmentation is a fundamental vision task underlying numerous downstream applications. Recent promptable segmentation models, such as Segment Anything M

From pre-training to downstream performance: Does domain-specific pre-training make sense?

arXiv:2605.08819v1 Announce Type: new Abstract: Deep learning techniques have revolutionised medical imaging, improving diagnostic accuracy and enabling both more accurate and earlier disease detectio

researcharxiv-cs-cv

Tutorials

From Regression to Inference: Meta-Learning Predictors for Neural Architecture Search

arXiv:2605.09290v1 Announce Type: new Abstract: Prediction-based approaches are widely used in neural architecture search (NAS), where a predictor estimates the performance of candidate architectures

tutorialsarxiv-cs-lg

From Single-Step Edit Response to Multi-Step Molecular Optimization

arXiv:2605.10035v1 Announce Type: new Abstract: Conditional molecular optimization aims to edit a molecule to realize a specified property shift. In practice, structurally similar molecule data is sca

local-aiarxiv-cs-ai

From Spark to Fire: Modeling and Mitigating Error Cascades in LLM-Based Multi-Agent Collaboration

arXiv:2603.04474v2 Announce Type: replace-cross Abstract: Large Language Model-based Multi-Agent Systems (LLM-MAS) are increasingly applied to complex collaborative scenarios. However, their collabora

Tutorials

From Syntax to Semantics: Unveiling the Emergence of Chirality in SMILES Translation Models

arXiv:2605.09949v1 Announce Type: new Abstract: Understanding how chemical language models (CLMs) learn chemical meaning from molecular string representations, rather than only surface-level string pa

tutorialsarxiv-cs-lg

From Traditional Taggers to LLMs: A Comparative Study of POS Tagging for Medieval Romance Languages

arXiv:2605.09147v1 Announce Type: cross Abstract: Part-of-speech (POS) tagging for Medieval Romance languages remains challenging due to orthographic variation, morphological complexity, and limited a

FugSeg: Fast Uncertainty-aware Ground Segmentation for 3D Point Cloud

arXiv:2605.08952v1 Announce Type: new Abstract: In LiDAR-based environment perception systems, ground segmentation is a key preprocessing step supporting various applications such as mapping and navig

researcharxiv-cs-cv

Fully Decentralized Cooperative Multi-Agent Reinforcement Learning is A Context Modeling Problem

arXiv:2509.15519v2 Announce Type: replace Abstract: This paper studies fully decentralized cooperative multi-agent reinforcement learning, where each agent solely observes the states, its local action

Fully First-Order Algorithms for Online Bilevel Optimization

arXiv:2602.11665v2 Announce Type: replace Abstract: In this work, we study nonconvex-strongly convex online bilevel optimization (OBO) using only first-order oracle. Existing OBO algorithms are mainly

researcharxiv-cs-lg

Function-Space ADMM for Decentralized Federated Learning: A Control Theoretic Perspective

model-releasesarxiv-cs-lg

arXiv:2605.09356v1 Announce Type: new Abstract: Decentralized federated learning (FL) is a promising approach for training machine learning models on sensor networks, Internet of Things (IoT) devices,

Functional Graphs for Predicting and Explaining Goal Failure in Sparse Goal-Conditioned RL

arXiv:2605.09335v1 Announce Type: new Abstract: Sparse goal-conditioned reinforcement learning can produce policies whose failures are hidden by aggregate success rates. We analyze trained goal-condit

safetyarxiv-cs-lg

Functional Stable Model Semantics and Answer Set Programming Modulo Theories

arXiv:2605.09524v1 Announce Type: new Abstract: Recently there has been an increasing interest in incorporating ``intensional'' functions in answer set programming. Intensional functions are those who

Functional Subspace, where language models can use vector algebra to solve problems

arXiv:2602.01687v2 Announce Type: replace-cross Abstract: Large language models (LLMs) were invented for natural language tasks such as translation, but they have proved that they can perform highly c

FunnelNet: An End-to-End Deep Learning Framework to Monitor Digital Heart Murmur in Real-Time

arXiv:2405.09570v2 Announce Type: replace-cross Abstract: Heart murmurs are abnormal sounds caused by turbulent blood flow in the heart. Several diagnostic methods are available to detect heart murmur

applicationsarxiv-cs-lg

G-Zero: Self-Play for Open-Ended Generation from Zero Data

arXiv:2605.09959v1 Announce Type: cross Abstract: Self-evolving LLMs excel in verifiable domains but struggle in open-ended tasks, where reliance on proxy LLM judges introduces capability bottlenecks

GAMBIT: A Three-Mode Benchmark for Adversarial Robustness in Multi-Agent LLM Collectives

model-releasesarxiv-cs-cl

arXiv:2605.09027v1 Announce Type: new Abstract: In multi-agent systems (MAS), a single deceptive agent can nullify all gains of an agentic AI collective and evade deployed defenses. However, existing

GameChat: Multi-LLM Dialogue for Safe, Agile, and Socially Optimal Multi-Agent Navigation in Constrained Environments

arXiv:2503.12333v2 Announce Type: replace Abstract: Safe, agile, and socially compliant multi-robot navigation in cluttered and constrained environments remains a critical challenge. This is especiall

agentsarxiv-cs-ro

Gate-and-Merge: Zero-shot Compositional Personalization of Vision Language Models

arXiv:2605.08702v1 Announce Type: cross Abstract: This paper tackles compositional personalization of vision-language models (VLMs). In this problem, multiple user-defined concepts must be recognized

GELATO: Generative Entropy- and Lyapunov-based Adaptive Token Offloading for Device-Edge Speculative LLM Inference

arXiv:2605.10124v1 Announce Type: cross Abstract: The recent growth of on-device Large Language Model (LLM) inference has driven significant interest in device-edge collaborative LLM inference. As a p

GemDepth: Geometry-Embedded Features for 3D-Consistent Video Depth

arXiv:2605.10525v1 Announce Type: new Abstract: Video depth estimation extends monocular prediction into the temporal domain to ensure coherence. However, existing methods often suffer from spatial bl

safetyarxiv-cs-cv

Gemini’s biggest new features are all about controlling your phone

model-releasesthe-verge-ai

It is, once again, Gemini season. Google is announcing a host of new Gemini features during its pre-I/O Android showcase, many of which aim to help use your phone for you. You'll find Gemini in more p

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

Gender Fairness in Audio Deepfake Detection: Performance and Disparity Analysis

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

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

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

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

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

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

model-releasesarxiv-cs-lg

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

model-releasesarxiv-cs-lg

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