All entries

arXiv:2505.13741v2 Announce Type: replace Abstract: Direct training of Spiking Neural Networks (SNNs) on neuromorphic hardware can greatly reduce energy costs compared to GPU-based training. However,

hardwarearxiv-cs-cv

FS-I2P:A Hierarchical Focus-Sweep Registration Network with Dynamically Allocated Depth

DGX agent

arXiv:2605.07607v1 Announce Type: new Abstract: Image-to-point cloud registration is often challenged by viewpoint changes, cross-modal discrepancies, and repetitive textures, which induce scale ambig

researcharxiv-cs-cv

11 May 2026

Functional-prior-based Bayesian PDE-constrained inversion using PINNs

arXiv:2605.07060v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) provide a mesh-free framework for solving PDE-constrained inverse problems, but their extension to Bayesian i

researcharxiv-cs-lg

Future-proof your data strategy: AlloyDB adds PostgreSQL 18 and new Extended Support

As you look out at your 2026 infrastructure roadmap, your goal is to balance the need for rapid innovation with operational stability. You shouldn't have to choose between adopting the latest database

safetygoogle-cloud-ai

Future Validity is the Missing Statistic: From Impossibility to Phi-Estimation for Grammar-Faithful Speculative Decoding

arXiv:2605.07698v1 Announce Type: new Abstract: Grammar-constrained generation is often combined with local vocabulary masking and speculative decoding, but the resulting sampling law is not the gramm

local-aiarxiv-cs-lg

GAD in the Wild: Benchmarking Graph Anomaly Detection under Realistic Deployment Challenges

arXiv:2605.07133v1 Announce Type: cross Abstract: Graph Anomaly Detection (GAD) is a critical task in graph machine learning with vital applications in financial fraud detection and social platform go

GameGen-Verifier: Parallel Keypoint-Based Verification for LLM-Generated Games via Runtime State Injection

arXiv:2605.07442v1 Announce Type: new Abstract: LLM-based game generation promises to turn natural-language specifications into executable games, but progress is limited by the lack of reliable automa

agentsarxiv-cs-lg

gamma-weakly heta-up-concavity: A Unified Framework for Non-Convex Optimization Beyond DR-Submodular and OSS Functions

arXiv:2602.13506v2 Announce Type: replace-cross Abstract: Optimizing non-convex functions is a fundamental challenge across machine learning and combinatorial optimization. We introduce and study gamm

researcharxiv-cs-ai

GASim: A Graph-Accelerated Hybrid Framework for Social Simulation

arXiv:2605.07692v1 Announce Type: new Abstract: Large-scale social simulators are essential for studying complex social patterns. Prior work explores hybrid methods to scale up simulations, combining

safetyarxiv-cs-ai

Gated QKAN-FWP: Scalable Quantum-inspired Sequence Learning

arXiv:2605.06734v1 Announce Type: cross Abstract: Fast Weight Programmers (FWPs) encode temporal dependencies through dynamically updated parameters rather than recurrent hidden states. Quantum FWPs (

Hardware

GATO: GPU-Accelerated and Batched Trajectory Optimization for Scalable Edge Model Predictive Control

arXiv:2510.07625v2 Announce Type: replace Abstract: While Model Predictive Control (MPC) delivers strong performance across robotics applications, solving the underlying (batches of) nonlinear traject

hardwarearxiv-cs-ro

GazeVLM: Active Vision via Internal Attention Control for Multimodal Reasoning

arXiv:2605.07817v1 Announce Type: cross Abstract: Human visual reasoning is governed by active vision, a process where metacognitive control drives top-down goal-directed attention, dynamically routin

GC-ART: Global Learnable Second-Order Rational Tone Curves for Illumination Robustness

model-releasesarxiv-cs-cv

arXiv:2605.07329v1 Announce Type: new Abstract: We introduce GC-ART (Global Curve Adaptive Rational Tone-mapping), a lightweight differentiable pre-processing module for robust image classification. G

GEM: Generating LiDAR World Model via Deformable Mamba

arXiv:2605.07326v1 Announce Type: new Abstract: World models, which simulate environmental dynamics and generate sensor observations, are gaining increasing attention in autonomous driving. However, p

agentsarxiv-cs-cv

Generalised Linear Models in Deep Bayesian RL with Learnable Basis Functions

arXiv:2512.20974v3 Announce Type: replace-cross Abstract: Bayesian Reinforcement Learning (BRL), a subclass of Meta-Reinforcement Learning (Meta-RL), provides a principled framework for generalisation

safetyarxiv-cs-ai

Generalising Travel Time Prediction To Varying Route Choices In Urban Networks

arXiv:2605.06918v1 Announce Type: cross Abstract: Previous methods that predict system-wide travel time, predominantly grounded in graph neural networks, remain limited to typical and recurring demand

researcharxiv-cs-lg

Generalized Euler Logarithm and its Applications in Machine Learning: Natural Gradient, Backpropagation, Generalized EG, Mirror Descent and OLPS

arXiv:2502.17500v3 Announce Type: replace-cross Abstract: This paper investigates in depth the fundamental properties of the two-parameter generalized Euler logarithm and its inverse, the associated d

Generate an image of the scariest thing you could possibly imagine scribbled into a child's coloring book

This Reddit post from r/ChatGPT likely discusses a creative prompt experiment where users attempted to get ChatGPT or similar AI image generation tools to create disturbing or horror-themed content by

industryr-chatgpt

Generate split-stack videos like this in a single click. The basic setup is simple, just upload an image and the system takes care of the re…

Generate split-stack videos like this in a single click. The basic setup is simple, just upload an image and the system takes care of the rest. Want more control? Switch to graph mode and fine-tune ea

local-aicomfyui--x

Generating training datasets for legal chatbots in Korean

arXiv:2605.07432v1 Announce Type: new Abstract: Chatbots are robots that can communicate with humans using text or voice signals. Legal chatbots improve access to justice, since legal representation a

local-aiarxiv-cs-cl

Generative Modeling with Flux Matching

arXiv:2605.07319v1 Announce Type: cross Abstract: We introduce Flux Matching, a new paradigm for generative modeling that generalizes existing score-based models to a broader family of vector fields t

researcharxiv-cs-ai

Applications

Geometric Analysis of Neural Regression Collapse via Intrinsic Dimension

arXiv:2510.01105v2 Announce Type: replace Abstract: Neural multivariate regression underpins a wide range of domains, including control, robotics, and finance, yet the geometry of its learned represen

applicationsarxiv-cs-lg

Geometric Kolmogorov--Arnold Network (GeoKAN)

arXiv:2605.06740v1 Announce Type: cross Abstract: We introduce Geometric Kolmogorov--Arnold Networks (GeoKANs), a family of geometry-aware KAN-type models in which approximation is carried out in lear

local-aiarxiv-cs-ai

GESR: Graph-Based Edge Semantic Reconstruction for Stealthy Communication Detection with Benign-Only Training

arXiv:2605.07536v1 Announce Type: cross Abstract: Detecting stealthy malicious communications from flow logs under benign-only training remains a critical challenge in network security. Malicious comm

local-aiarxiv-cs-lg

GitLab announces layoffs, saying they are 'not an AI optimization or cost cutting exercise', and plans to cut the number of countries it operates in (Sarah Frier/Bloomberg)

Sarah Frier / Bloomberg: GitLab announces layoffs, saying they are “not an AI optimization or cost cutting exercise”, and plans to cut the number of countries it operates in — GitLab Inc., which makes

agentstechmeme

Give our early preview of Computer Use (with ANY model) a try today! Built into the latest Hermes Agent and powered by @trycua - opens the d…

Give our early preview of Computer Use (with ANY model) a try today! Built into the latest Hermes Agent and powered by @trycua - opens the door to any model, not just the frontier models in special mo

agentsnous-research--x

GLiGuard: Schema-Conditioned Classification for LLM Safeguard

model-releasesarxiv-cs-cl

arXiv:2605.07982v1 Announce Type: new Abstract: Ensuring safe, policy-compliant outputs from large language models requires real-time content moderation that can scale across multiple safety dimension

Globally Optimal Training of Spiking Neural Networks via Parameter Reconstruction

arXiv:2605.08022v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) have been proposed as biologically plausible and energy-efficient alternatives to conventional Artificial Neural Networ

GM plans to lay off IT workers in an effort to trim costs and bring in staff with skills in other tech areas; sources: the cuts will affect 500 to 600 employees (David Welch/Bloomberg)

David Welch / Bloomberg: GM plans to lay off IT workers in an effort to trim costs and bring in staff with skills in other tech areas; sources: the cuts will affect 500 to 600 employees — General Moto

industrytechmeme

Goal-Conditioned Decision Transformer for Multi-Goal Offline Reinforcement Learning

arXiv:2410.06347v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) in robotics faces significant hurdles regarding sample efficiency and generalization across varying goals. While O

🤔Going to be in Vancouver tomorrow? 🧐Curious about whether or not scaling AI is a bad bet? 😎Catch TPN founder @zacharykarabell's chat wit…

🤔Going to be in Vancouver tomorrow? 🧐Curious about whether or not scaling AI is a bad bet? 😎Catch TPN founder @zacharykarabell's chat with @GaryMarcus at @WebSummit at 10:20am. 🎟️Get your tickets here

safetygary-marcus--x

Goldilocks RL: Tuning Task Difficulty to Escape Sparse Rewards for Reasoning

arXiv:2602.14868v2 Announce Type: replace-cross Abstract: Reinforcement learning has emerged as a powerful paradigm for unlocking reasoning capabilities in language models. However, relying on sparse

researcharxiv-cs-ai

Gonna keep retweeting, because this flawed move never dies:

Gonna keep retweeting, because this flawed move never dies: AI hype has become a giant game of bait and switch. the bait: we are going to make an AI that can solve any problem a expert human could sol

safetygary-marcus--x

Google says criminals used AI to build a working zero-day exploit for the first time

model-releasessiliconangle

Criminal hackers have used artificial intelligence to develop a working zero-day exploit, the first confirmed case of its kind, according to a report released today by Google LLC’s Google Threat Intel

Google stopped a zero-day hack that it says was developed with AI

For the first time, Google says it has spotted and stopped a zero-day exploit developed with AI. According to a report from Google Threat Intelligence Group (GTIG), 'prominent cyber crime threat actor

industrythe-verge-ai

Google's TIG reports the first known example of hackers using AI to discover and weaponize a zero-day; TIG's chief analyst says 'this is the tip of the iceberg' (Dustin Volz/New York Times)

Dustin Volz / New York Times: Google's TIG reports the first known example of hackers using AI to discover and weaponize a zero-day; TIG's chief analyst says “this is the tip of the iceberg” — The com

industrytechmeme

Google's TIG says it likely thwarted the use of an AI-generated zero-day in a 'mass exploitation event' and tools like OpenClaw are being used to find exploits (Samantha Subin/CNBC)

Samantha Subin / CNBC: Google's TIG says it likely thwarted the use of an AI-generated zero-day in a “mass exploitation event” and tools like OpenClaw are being used to find exploits — Google's Threat

industrytechmeme

GPO-V: Jailbreak Diffusion Vision Language Model by Global Probability Optimization

arXiv:2605.07399v1 Announce Type: new Abstract: Diffusion Vision-Language Models (dVLMs), built upon the non-causal foundations of Diffusion Large Language Models (dLLMs), have demonstrated remarkable

safetyarxiv-cs-cv

Gradient-Based LoRA Rank Allocation Under GRPO: An Empirical Study

model-releasesarxiv-cs-cl

arXiv:2605.07366v1 Announce Type: new Abstract: Adaptive rank allocation for LoRA, allocating more parameters to important layers and fewer to unimportant ones, consistently improves efficiency under

Gradient Extrapolation-Based Policy Optimization

arXiv:2605.06755v1 Announce Type: cross Abstract: Reinforcement learning is widely used to improve the reasoning ability of large language models, especially when answers can be automatically checked.

Gradient Starvation in Binary-Reward GRPO: Why Group-Mean Centering Fails and Why the Simplest Fix Works

model-releasesarxiv-cs-lg

arXiv:2605.07689v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) is a standard algorithm for reinforcement learning from verifiable rewards, but its group-mean-centered advant

GRAPE: Let GRPO Supervise Query Rewriting by Ranking for Retrieval

arXiv:2509.23370v2 Announce Type: replace Abstract: The CLIP model has established itself as a cornerstone of large-scale retrieval systems. However, its performance often degrades under distributiona

safetyarxiv-cs-cv

Graph Representation Learning Augmented Model Manipulation on Federated Fine-Tuning of LLMs

model-releasesarxiv-cs-lg

arXiv:2605.07961v1 Announce Type: new Abstract: Federated fine-tuning (FFT) has emerged as a privacy-preserving paradigm for collaboratively adapting large language models (LLMs). Built upon federated

Graph-Structured Hyperdimensional Computing for Data-Efficient and Explainable Process-Structure-Property Prediction

arXiv:2605.07999v1 Announce Type: cross Abstract: Multiphoton photoreduction enables high-fidelity fabrication of complex 3D microstructures, yet reliable process-structure-property (PSP) prediction r

GraphDC: A Divide-and-Conquer Multi-Agent System for Scalable Graph Algorithm Reasoning

arXiv:2605.06671v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated strong potential for many mathematical problems. However, their performance on graph algorithmic tasks is

agentsarxiv-cs-ai

GraphFusion3D: Dynamic Graph Attention Convolution with Adaptive Cross-Modal Transformer for 3D Object Detection

arXiv:2512.02991v2 Announce Type: replace Abstract: Despite significant progress in 3D object detection, point clouds remain challenging due to sparse data, incomplete structures, and limited semantic

researcharxiv-cs-cv

GRAPHLCP: Structure-Aware Localized Conformal Prediction on Graphs

arXiv:2605.08074v1 Announce Type: new Abstract: Conformal prediction (CP) provides a distribution-free approach to uncertainty quantification with finite-sample guarantees. However, applying CP to gra

local-aiarxiv-cs-lg

GraphReAct: Reasoning and Acting for Multi-step Graph Inference

arXiv:2605.07357v1 Announce Type: new Abstract: Reasoning-acting frameworks enhance large language models (LLMs) by interleaving reasoning with actions for dynamic information acquisition. However, ex