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arXiv:2609.08607v1 Announce Type: new Abstract: We present GOLF, the first-place solution to the SHOW3D Interaction Field Estimation Challenge at HANDS@ECCV 2026. Given synchronized egocentric stereo

local-aiarxiv-cs-cv

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Good work on improving memory for long-horizon agents. They separate two things that agent memory papers usually collapse into one. How memo…

DGX agent

Good work on improving memory for long-horizon agents. They separate two things that agent memory papers usually collapse into one. How memories get merged when they are written, and how retrieved con

agentsdair-ai--x

9 Sept 2026

Google is a Leader in the 2026 Gartner® Magic Quadrant™ for Enterprise AI Assistants

model-releasesgoogle-cloud-ai

We are excited to share that Gartner has named Google a Leader in its inaugural 2026 Magic Quadrant for Enterprise AI Assistants. In this comprehensive evaluation of top enterprise AI assistant vendor

GPT-6 Astra, Looped Transformers, and Hidden Reasoning

researchsebastian-raschka

GPT‑6 Astra is OpenAI’s latest flagship model, outperforming GPT‑5.6 across virtually all common benchmarks—most noticeably in math, coding, and especially 3‑D rendering/animation tasks. The architect

Hardware

GPU-Enabled Large-Scale Optimization Using Randomized Linear Algebra

arXiv:2609.08136v1 Announce Type: new Abstract: This paper introduces rlaopt, a PyTorch-based package for large-scale optimization and scientific computing using randomized numerical linear algebra (R

hardwarearxiv-cs-lg

GradeTrap: Authority Cues in Images Shift VLM Judgments Despite Explicit Instructions to Ignore Them

arXiv:2609.06058v1 Announce Type: new Abstract: As vision-language models (VLMs) become increasingly capable and are deployed in consequential real-world settings, they must evaluate evidence independ

GRAN-TED: Generating Robust, Aligned, and Nuanced Text Embedding for Diffusion Models

arXiv:2512.15560v3 Announce Type: replace Abstract: The text encoder is a critical component of text-to-image and text-to-video diffusion models, fundamentally determining the semantic fidelity of the

Granular-Ball Quantum Clustering for Resource-Efficient and Robust Learning

arXiv:2609.06016v1 Announce Type: new Abstract: Quantum clustering aims to exploit quantum feature representations to uncover complex data structures beyond conventional Euclidean geometry. Yet this s

Graph-Based Safe Reinforcement Learning for Multi-Agent Systems with Time-Varying Topology

arXiv:2609.08802v1 Announce Type: new Abstract: This paper presents a graph-based safe multi-agent reinforcement learning (MARL) framework for cooperative navigation with time-varying topology. To add

safetyarxiv-cs-ro

Graph neural networks and the energetic cavity method for combinatorial optimization

arXiv:2609.07456v1 Announce Type: cross Abstract: We study the use of graph neural networks (GNNs) for finding approximate ground states of Ising models. Efficiently finding these ground states is of

GraphFAS: A Distributed System for Automated Graph Feature Generation and Selection in Industrial Transaction Networks

arXiv:2609.08970v1 Announce Type: new Abstract: Industrial fraud detection often relies on costly expert-crafted features that overlook graph-structured relational signals, while GNNs often do not mee

GraphNOSE: A Graph Transformer in Olfaction

arXiv:2609.05694v1 Announce Type: new Abstract: Predicting olfactory qualities from molecular structure is an open problem in chemoinformatics. Although linear models can link molecular features to od

Great study on what actually predicts vibe-coding ability. 100 tertiary-level students completed measures of computer-science achievement, d…

Great study on what actually predicts vibe-coding ability. 100 tertiary-level students completed measures of computer-science achievement, domain-general cognitive skills and written-communication pro

researchdair-ai--x

Grounded and Faithful P&ID Reasoning: Constraining Vision-Language Models with Recovered Evidence Graphs

arXiv:2609.05880v1 Announce Type: new Abstract: Piping and Instrumentation Diagrams (P&IDs) are the authoritative maps of process plants: isolation, maintenance, and HAZOP decisions depend on what con

GSComplete: Gaussian Splat Completion with 2D Diffusion Priors

arXiv:2609.08449v1 Announce Type: new Abstract: Gaussian splats provide a fast, high-fidelity representation for 3D objects but are often constructed from incomplete input data in practice, leaving mi

researcharxiv-cs-cv

Guiding Worker Self-Selection in Crowdsourcing Contests: An LLM-Augmented Algorithmic Approach

arXiv:2609.07749v1 Announce Type: new Abstract: Crowdsourcing platforms coordinate large pools of online workers who strategically choose which contests to enter and how much effort to invest. This se

Hardware Trojan Threats to Multi-Chiplet Photonic Neural Network Accelerators

arXiv:2609.06796v1 Announce Type: cross Abstract: Multi-chiplet photonic neural network accelerators (MCPNAs) combine photonic computation, photonic communica-tion, and heterogeneous chiplet integrati

Harnessing CLIP and DINO: An Uncertainty-Aware Cascaded Fusion Network for Generalizable Deepfake Image Detection

arXiv:2609.07670v1 Announce Type: new Abstract: The growing realism and accessibility of manipulated and generated faces threaten the trustworthiness of digital media. To detect such forgeries, deepfa

Having trouble with models just cutting off suddenly when responding.

I'm using two different models. One Gemma 4 and the other qwen 3.5. Both of them are responding to my input either by silence ('thought for a moment.... then nothing') or nonsense: <|turn>user <|turn>

model-releasesr-ollama

HB-PVI: A Hierarchical Bayesian Personalization and Value-of-Information Framework for Complex Activity Recognition

arXiv:2609.05582v1 Announce Type: new Abstract: Personalization can improve activity-recognition performance, but participant-specific gains are heterogeneous, and every additional calibration label h

safetyarxiv-cs-lg

HealthLoopQA: A Context-Aware Question Answering Benchmark for Interpreting Wearable Monitoring Data in Diabetes Care

arXiv:2609.06976v1 Announce Type: new Abstract: As medical wearables become integrated into daily chronic disease care, effectively interpreting longitudinal monitoring data is essential for patients

Heat Field Signatures: From Point Clouds to Smooth Geometry

arXiv:2609.07975v1 Announce Type: new Abstract: Bringing multiscale geometric analysis directly to irregular point clouds remains difficult: quantities such as local dimension, anisotropy, density var

Heat Kernel Textures: the Geodesic Gaussians That Do Not Splat

arXiv:2609.07557v1 Announce Type: new Abstract: 3D Gaussian Splatting has recently revolutionised novel view synthesis as well as many other 3D vision methods and applications. Drawing inspiration fro

researcharxiv-cs-cv

Here's a link to the article: https://magazine.sebastianraschka.com/p/gpt-6-astra-looped-transformers-and

researchsebastian-raschka--x

Sebastian Raschka’s September 2026 article introduces **GPT‑6 *Astra***, a next‑generation language model that expands upon the Transformer backbone with a novel *looped* architecture—allowing multipl

HGGT: Robust and Flexible 3D Hand Mesh Reconstruction from Uncalibrated Images

arXiv:2603.23997v3 Announce Type: replace Abstract: Recovering high-fidelity 3D hand geometry from images is a critical task in computer vision, holding significant value for domains such as robotics,

tutorialsarxiv-cs-cv

Agents

Hi-FLoop: Hierarchical State-Feedback Loops for Multi-Timescale World Modeling

arXiv:2609.08796v1 Announce Type: new Abstract: Multi-agent traffic simulation seeks diverse, coordinated, and physically realistic futures from maps and observed history. Long-horizon closed-loop gen

agentsarxiv-cs-cv

Agents

HiBRIDGE: A Hierarchical Bayesian Neural Network Framework for Interpretable Dialogue Management in Group-Robot Interaction

arXiv:2609.08678v1 Announce Type: new Abstract: In multi-party human-robot interaction, a robot must continuously decide whom to address and what to say to participate effectively in the conversation.

agentsarxiv-cs-ro

Hidden in Plain Sight: The Overlooked Significance of Canonical Elements for Extreme LLM Sparsity

arXiv:2609.06557v1 Announce Type: new Abstract: Large language models (LLMs) are often considered fragile under aggressive sparsification, and maintaining reliable performance typically requires stick

Hierarchical Fourier Approximation for Variational Quantum Distribution Learning

arXiv:2609.06307v1 Announce Type: cross Abstract: We study variational quantum distribution learning through a hierarchy of Walsh--Fourier approximations on the Boolean cube. At each level, a selected

Hierarchical Prompt Injector for Domain Generalization Segmentation

arXiv:2609.05864v1 Announce Type: new Abstract: Domain Generalized Semantic Segmentation (DGSS) is a challenging task, as vision models often rely on low-level appearance cues that change across domai

High-dimensional Linear Bandits with Knapsacks

arXiv:2311.01327v3 Announce Type: replace Abstract: We investigate the contextual bandits with knapsack (CBwK) problem in a high-dimensional linear setting, where the feature dimension can be very lar

High-Magnetization Sampling at Low Temperatures: Ising Models and Bayesian Sparse Linear Regression

arXiv:2609.08873v1 Announce Type: cross Abstract: Sparsity is a powerful structural resource in optimization and statistics. We develop frameworks for leveraging sparsity in sampling problems over the

tutorialsarxiv-cs-lg

HoneyRoute: Honeypot-Model Routing for Adversarial LLM Serving

arXiv:2609.08306v1 Announce Type: cross Abstract: We introduce HoneyRoute, an inference-serving layer that detects whether an incoming request is malicious and, if so, routes it to a dedicated honeypo

HOPE: Heterophily-Aware Open-Set Node Classification with Pseudo-Extrapolation

arXiv:2609.08685v1 Announce Type: new Abstract: Standard open-set node classification methods rely on the homophily assumption, where connected nodes share labels. However, real-world graphs are often

How Does Parameter Pruning Reshape DNN Representations? An Interaction-Driven Exploration

arXiv:2609.06483v1 Announce Type: new Abstract: This study focuses on the scientific problem of understanding internal factors that govern the diverse performance degradation of deep neural networks (

How Goodfire used Ai2’s open post-training stack to trace unwanted model behavior

Goodfire used Ai2’s fully open post-training stack to predict LLM behavioral changes, trace unwanted model behavior back to individual training examples, and test targeted fixes without sacrificing br

researchai2

How Heurist Finance built an AI-native investment workbench on Amazon Bedrock AgentCore

Learn how Heurist built Heurist Finance, a conversational AI investment workbench, on Amazon Bedrock AgentCore. This customer story shows how AgentCore payments, Identity, Memory, Code Interpreter, an

tutorialsaws-ml-blog

How Long Until Your Robot Ignores You? A Safety Benchmark for LLM Orchestrators in Human-Humanoid Collaboration

model-releasesarxiv-cs-ro

arXiv:2609.07288v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly employed to orchestrate robot behavior through natural-language interfaces, yet no benchmark exists to eva

How to Backdoor Image Knowledge Distillation

arXiv:2504.21323v3 Announce Type: replace-cross Abstract: Knowledge distillation is widely used to transfer behavior from a large teacher model to a smaller student. It is often assumed to be safe whe

tutorialsarxiv-cs-lg

How to Learn from What a Human Would Avoid? Intervention-Aware World Models with Real-World RL for Dexterous Manipulation

arXiv:2609.06009v1 Announce Type: new Abstract: Multi-fingered dexterous manipulation remains a frontier for real-world reinforcement learning (RL) due to the high-dimensional action space and the pro

safetyarxiv-cs-ro

How to Make the Gradient Mapping Small for Constrained Stochastic Min-Max Problems and Beyond

arXiv:2609.08380v1 Announce Type: cross Abstract: We study the stochastic first-order oracle complexity for constrained or regularized convex-concave min-max optimization and stochastic monotone varia

tutorialsarxiv-cs-lg

How Well Can Modern LLMs Act as Agent Cores in Radiology Environments?

arXiv:2412.09529v4 Announce Type: replace Abstract: Radiology, with its heterogeneous modalities, anatomies, and evolving protocols, is a natural yet high-stakes testbed for agentic AI. As LLMs grow m

Agents

Human-Aware Target Tracking and Navigation: Fusing Kinematic State Estimation with Structural Map Constraints

arXiv:2609.07091v1 Announce Type: new Abstract: Autonomous mobile robots performing person-following tasks often suffer from temporary occlusions and sensor track loss in dynamic environments. This re

agentsarxiv-cs-ro

Human-Centric Image Captioning with Subject-Centered Spatial Understanding

arXiv:2609.08300v1 Announce Type: new Abstract: While multimodal large language models (MLLMs) achieve remarkable performance on generic image captioning, they frequently suffer from structural halluc

Human-Robot Interaction and Perceived Irrationality: A Study of Trust Dynamics and Error Acknowledgment

arXiv:2403.14293v3 Announce Type: replace Abstract: As robots become increasingly integrated into various industries, understanding how humans respond to robotic failures is critical. This study syste

researcharxiv-cs-ro

HyCO: A Hybrid Neural Solver for Combinatorial Optimization

arXiv:2609.07990v1 Announce Type: new Abstract: Sequential reinforcement learning (RL) solvers and global diffusion model (DM) solvers for neural combinatorial optimization exhibit complementary failu

safetyarxiv-cs-lg

Hyperelastic constitutive model discovery with differentiable finite elements and structure-preserving neural networks

arXiv:2603.26517v2 Announce Type: replace-cross Abstract: The discovery of constitutive laws from experimentally accessible measurements is a central problem in nonlinear computational mechanics. Many

Hyperparameter Scaling Laws Across MoE Sparsity

arXiv:2609.08690v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models expand model capacity without a proportional increase in training compute, but increasing sparsity makes reliable hyperp