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arXiv:2602.07253v2 Announce Type: replace Abstract: Detecting hallucinations in large language models is a critical open problem with significant implications for safety and reliability. While existin

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From Prompt Injection to Persistent Control: Defending Agentic Harness Against Trojan Backdoors

DGX agent

arXiv:2605.31042v1 Announce Type: cross Abstract: LLM agents are evolving from conversational chatbots to operational tools in real-world workspaces. In local agentic harnesses, an LLM can read and wr

model-releasesarxiv-cs-ai

1 Jun 2026

From Weak Cues to Real Identities: Evaluating Inference-Driven De-Anonymization in LLM Agents

arXiv:2603.18382v2 Announce Type: replace Abstract: Anonymization is often assumed to protect privacy once explicit identifiers are removed, because re-identification has historically required special

FSM-Net: An Efficient Frequency-Spatial Network for Real-World Deblurring

model-releasesarxiv-cs-cv

arXiv:2605.31400v1 Announce Type: new Abstract: Real-world image deblurring demands both high-fidelity restoration and computational efficiency, a balance existing methods often struggle to achieve. I

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning

arXiv:2605.30375v1 Announce Type: cross Abstract: High-fidelity computational fluid dynamics is essential for aerospace design, but engineering-scale simulations of practical three-dimensional aircraf

Function2Scene: 3D Indoor Scene Layout from Functional Specifications

arXiv:2605.30819v1 Announce Type: new Abstract: Most text-driven 3D indoor scene synthesis methods generate rooms from object-centric prompts, asking what furniture should be placed rather than how th

tutorialsarxiv-cs-cv

Functional Attention: From Pairwise Affinities to Functional Correspondences

arXiv:2605.31559v1 Announce Type: new Abstract: Learning mappings between infinite-dimensional function spaces, or operator learning, is essential for many machine learning applications. Although tran

Functional MRI Time Series Generation via Wavelet-Based Image Transform and Spectral Flow Matching for Brain Disorder Identification

arXiv:2605.30387v1 Announce Type: cross Abstract: Functional Magnetic Resonance Imaging (fMRI) provides non-invasive access to dynamic brain activity by measuring blood oxygen level-dependent (BOLD) s

Functorial Neural Architectures from Higher Inductive Types

arXiv:2603.16123v2 Announce Type: replace-cross Abstract: Neural networks often learn the parts of a task but fail on novel combinations of those parts. We argue that this failure is architectural: a

tutorialsarxiv-cs-ai

G-STAR: End-to-End Global Speaker-Tracking Attributed Recognition

arXiv:2603.10468v2 Announce Type: replace-cross Abstract: We study timestamped speaker-attributed automatic speech recognition (SA-ASR) for long-form, multi-party speech with overlap. In this setting,

Gait2Hip-60: A Unified Deep Learning Benchmark for Predicting Hip Muscle Forces and Joint Moments from Multi-Cadence Gait Kinematics

model-releasesarxiv-cs-lg

arXiv:2605.30374v1 Announce Type: new Abstract: Estimating hip muscle forces and joint moments during gait typically relies on musculoskeletal simulation, which is informative but time-consuming and d

GaMi: Geometry-Agnostic Material Identification via Cross-Modal Subtractive Disentanglement

arXiv:2605.30818v1 Announce Type: cross Abstract: Non-contact material identification enables adaptive interaction for embodied intelligence yet faces challenges from geometry-induced variations (e.g.

Gap-K%: Measuring Top-1 Prediction Gap for Detecting Pretraining Data

arXiv:2601.19936v2 Announce Type: replace-cross Abstract: The opacity of massive pretraining corpora in Large Language Models (LLMs) raises significant privacy and copyright concerns, making pretraini

GEM-Bench: A Benchmark for Ad-Injected Response Generation within Generative Engine Marketing

model-releasesarxiv-cs-cl

arXiv:2509.14221v3 Announce Type: replace-cross Abstract: Generative Engine Marketing (GEM) is an emerging ecosystem for monetizing generative engines, such as LLM-based chatbots, by seamlessly integr

Gemini’s new AI agent is about as good as Google’s demo

model-releasesthe-verge-ai

Google's new '24/7' AI agent, Gemini Spark, can be shockingly good at doing things on your behalf. But I'm not sure it's worth the financial cost and potential privacy tradeoffs. The company gave me a

Generalistic or Specific Embeddings, Which is Better? An Empirical Study on Search for Clinical Coding in Non-English Languages

arXiv:2605.30529v1 Announce Type: cross Abstract: Sentence-embedding models for semantic search are overwhelmingly developed and evaluated on English corpora. When applied to clinical retrieval in oth

Agents

Generalized Intention Modeling in Multi-Agent Reinforcement Learning

arXiv:2605.31318v1 Announce Type: new Abstract: Modeling an opponent's intent is critical for effective decision-making in non-cooperative, competitive, and general-sum multi-agent reinforcement learn

agentsarxiv-cs-lg

Generalizing Multi-Scale Time-Series Modeling with a Single Operator

arXiv:2605.31129v1 Announce Type: new Abstract: Multi-scale modeling has emerged as an effective design principle for time-series forecasting by capturing temporal dynamics at multiple resolutions. As

Generating and Refining Dynamic Evaluation Rubrics for LLM-as-a-Judge

arXiv:2605.30568v1 Announce Type: new Abstract: LLM-as-a-Judge is a scalable alternative to human evaluation, yet existing rubric-based methods rely on human-annotated data such as reference answers o

researcharxiv-cs-cl

Generating Graph-like Rules for Knowledge Graph Reasoning via Diffusion Models

arXiv:2605.30747v1 Announce Type: new Abstract: Logical rules constitute a cornerstone of knowledge graph (KG) reasoning, valued for their interpretability and ability to model relational patterns. Ho

Generating Reports or Repeating Templates? Measuring and Mitigating Template Collapse in 3D CT Report Generation

arXiv:2605.30984v1 Announce Type: cross Abstract: Modern 3D medical vision-language models (VLMs) can generate fluent radiology-style text while exhibit critically low pathology detection and output d

Generative Drifting is Secretly Score Matching: a Spectral and Variational Perspective

arXiv:2603.09936v2 Announce Type: replace Abstract: Generative Modeling via Drifting~itep{deng2026drifting} has recently achieved state-of-the-art one-step image generation through a kernel-based drif

tutorialsarxiv-cs-lg

Generative Models and Statistical Validation

arXiv:2605.30453v1 Announce Type: cross Abstract: Generative machine learning has become an essential tool in theoretical and experimental physics, especially in the context of fast surrogates and den

Generative Quantum Data Embeddings for Supervised Learning

arXiv:2605.30866v1 Announce Type: cross Abstract: Many practically relevant applications of quantum machine learning involve classical data, for which performance depends critically on how inputs are

tutorialsarxiv-cs-lg

Safety

Geometry-Aware Control Barrier Functions for Collision Avoidance via Bernstein Polynomial Approximations

arXiv:2605.30696v1 Announce Type: new Abstract: Safe navigation often relies on well-defined conditions based on the shape of robots and obstacles, and can be challenging when they have irregular geom

safetyarxiv-cs-ro

Applications

Geometry-based Schrodinger Bridges for Trustworthy Multimodal Fusion

arXiv:2605.31193v1 Announce Type: new Abstract: Real-world multimodal systems must be robust against low-quality data, such as sensor noise, incomplete multimodal data and conflicting inputs. However,

applicationsarxiv-cs-lg

GETA: Generalized Encrypted Traffic Analysis

arXiv:2605.31277v1 Announce Type: cross Abstract: Traditional traffic analysis is being fundamentally challenged by the rapid adoption of encryption, tunnelling, and privacy-preserving protocols, whic

Getting Started: 1. Update ComfyUI to the latest version [] 2. Open the Template library, then search for TripoSplat 3. Follow the note in t…

Getting Started: 1. Update ComfyUI to the latest version [] 2. Open the Template library, then search for TripoSplat 3. Follow the note in the workflow to download models 4. Load an image, then run th

local-aicomfyui--x

Applications

GGT-100K: Generative Ground Truth for Generalizable Real-World Image Restoration

arXiv:2605.31039v1 Announce Type: new Abstract: Real-world image restoration (IR) is bottlenecked by the scarcity of high-quality paired training data. Synthetic datasets are abundant but often fail t

applicationsarxiv-cs-cv

Gigascale Capital, a climate tech VC firm co-founded by former Meta CTO Mike Schroepfer, closed a $250M fund to back early-stage startups supporting the AI boom (Michelle Ma/Bloomberg)

Michelle Ma / Bloomberg: Gigascale Capital, a climate tech VC firm co-founded by former Meta CTO Mike Schroepfer, closed a 250M fund to back early-stage startups supporting the AI boom — Gigascale Cap

industrytechmeme

GitHub Copilot's new pricing model went into effect today, and many noted sticker shock with some saying a few hours of AI usage ate big chunks of monthly caps (Kyle Orland/Ars Technica)

Kyle Orland / Ars Technica: GitHub Copilot's new pricing model went into effect today, and many noted sticker shock with some saying a few hours of AI usage ate big chunks of monthly caps — In April,

industrytechmeme

Giving Sensors a Voice: Multimodal JEPA for Semantic Time-Series Embeddings

arXiv:2605.31580v1 Announce Type: new Abstract: Transformer-based architectures have advanced sequence modeling in language and vision, yet general-purpose representation learning for heterogeneous mu

Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink

arXiv:2601.19966v2 Announce Type: replace-cross Abstract: We introduce ELECTRAFI, a fast, end-to-end differentiable model for predicting periodic charge densities in crystalline materials. ELECTRAFI c

local-aiarxiv-cs-lg

Safety

GlucoFM: A Dual-Stream Foundation Model for Continuous Glucose Monitoring

arXiv:2605.30865v1 Announce Type: new Abstract: Continuous glucose monitoring (CGM) provides a dense view of daily metabolic physiology, yet existing generic time-series and CGM-specific foundation mo

safetyarxiv-cs-lg

Tools

Go to https://replit.com/free-business to redeem offer Available for a limited time only

Replit is promoting a limited-time business offer accessible through their website at replit.com/free-business. The offer details and specific terms are not specified in the title, but it likely invol

toolsreplit--x

Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go

model-releasesarxiv-cs-lg

arXiv:2511.10868v2 Announce Type: replace Abstract: Training data imbalance poses a major challenge for code LLMs. Most available data heavily over represents raw opensource code while underrepresenti

Goldfish: Monolingual Language Models for 350 Languages

model-releasesarxiv-cs-cl

arXiv:2408.10441v3 Announce Type: replace Abstract: For many low-resource languages, the only available language models are large multilingual models trained on many languages simultaneously. Despite

Good point

Good point Honestly Grok should be the best AI for creating bangers. Humans get good at posting from RL with Audience / Engagement Feedback Elon has the best dataset of rollouts for this by far And ma

industryelon-musk--x

Google plans to open its first physical Google Store outside of the US, in Tokyo's Omotesando district 'this summer', marking Google's 11th physical store (Damien Wilde/9to5Google)

Damien Wilde / 9to5Google: Google plans to open its first physical Google Store outside of the US, in Tokyo's Omotesando district “this summer”, marking Google's 11th physical store — After being excl

industrytechmeme

GPU Forecasters: Language Models as Selective Surrogates for Kernel Runtime Optimization

arXiv:2605.31464v1 Announce Type: cross Abstract: GPU kernels are the workhorse of modern deep learning, and optimizing them (via evolutionary search or coding agents) usually requires repeated measur

Gradient-Free Training of Spiking Neural Networks via Low-Rank Evolution Strategies

arXiv:2605.30361v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) offer compelling energy efficiency on neuromorphic hardware, yet their training remains challenging because the discret

GradMem: Learning to Write Context into Memory with Test-Time Gradient Descent

arXiv:2603.13875v2 Announce Type: replace Abstract: Many large language model applications require conditioning on long contexts. Transformers typically support this by storing a large per-layer KV-ca

researcharxiv-cs-cl

Graph-Conditioned Mixture of Graph Neural Network Experts for Traffic Forecasting

arXiv:2605.30486v1 Announce Type: cross Abstract: Spatio-temporal forecasting on sensor graphs is commonly tackled with a single backbone architecture applied uniformly across all nodes, although grap

Graph Energy Matching: Transport-Aligned Energy-Based Modeling for Graph Generation

arXiv:2603.23398v2 Announce Type: replace-cross Abstract: Generative modeling of discrete data, such as graphs, underpins many scientific and industrial applications, including molecular discovery and

Graph Machine Learning in the Era of Large Language Models (LLMs)

arXiv:2404.14928v3 Announce Type: replace-cross Abstract: Graphs play an important role in representing complex relationships in various domains like social networks, knowledge graphs, and molecular d

Graph Neural Networks Are Not Continuous Across Graph Resolutions

arXiv:2605.31315v1 Announce Type: new Abstract: We show that contrary to conventional wisdom in the community, graph neural networks (GNNs) are not continuous with respect to all natural modes of grap

GraphARC: A Comprehensive Benchmark for Graph-Based Abstract Reasoning

arXiv:2605.31031v1 Announce Type: new Abstract: Relational reasoning lies at the heart of intelligence, but existing benchmarks are typically confined to formats such as grids or text. We introduce Gr

Graphical einops: bridging tensor networks and computation graphs

arXiv:2605.31485v1 Announce Type: new Abstract: Architecture diagrams are ubiquitous in deep learning, but they are usually only representational: the tensor-program identities they suggest are still