Search: “models”

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

applicationsarxiv-cs-lg

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

Hypersolid: Emergent Vision Representations via Short-Range Repulsion

DGX agent

arXiv:2601.21255v2 Announce Type: replace Abstract: A central problem in self-supervised learning is preventing representation collapse. Most methods avoid it through global mechanisms, such as contra

safetyarxiv-cs-cv

9 Sept 2026

I put together a mega write-up on GPT-6 Astra & looped transformers. How looped transformers / recurrent depth works, cost-tradeoffs, whethe…

researchsebastian-raschka--x

I put together a mega write-up on GPT-6 Astra & looped transformers. How looped transformers / recurrent depth works, cost-tradeoffs, whether it hides reasoning traces, with lots of figures and a tour

IM-ENGINE: Image Editing for Embodied Data Generation

arXiv:2609.06279v1 Announce Type: cross Abstract: Learning-based manipulation requires supervision that is both semantically meaningful and physically executable, but current data pipelines often prov

Information-Guided Safe Reinforcement Learning for Autonomous Gas Source Localization using sUAS

arXiv:2609.05569v1 Announce Type: new Abstract: The autonomous localization of fugitive gas emissions using small Unmanned Aircraft Systems (sUAS) constitutes a fundamentally ill-posed inverse problem

Infrastructure-based Monocular 3D Vehicle Localization Framework with Experimental Validation

arXiv:2609.05523v1 Announce Type: new Abstract: This paper presents a one-stage learning framework that maps monocular roadside-camera images directly to vehicle states in a ground-fixed coordinate fr

Introducing HALC: A general pipeline for the systematic and reliable construction of prompts for automated coding with LLMs in the computational social sciences

arXiv:2507.21831v2 Announce Type: replace-cross Abstract: LLMs are seeing widespread use for task automation, including automated coding in the social sciences. However, even though researchers have p

Introductory Notes on Learning^2

arXiv:2609.06546v1 Announce Type: cross Abstract: Although machine learning can be used to predict the evolution of physical systems from data, a formulation that learns only the system state at each

KBBQ: A Predictive Noise Law and the Limits of Spectrum Flattening in FP4 Quantization

arXiv:2609.08135v1 Announce Type: new Abstract: We develop a second-order theory of quantization noise in matrix multiplication in which the quantization format is characterized by the variance it ass

Knowledge-Guided Hierarchical Policy Learning for High-Precision Cylindrical Assembly under Tight Tolerances

arXiv:2609.06522v1 Announce Type: new Abstract: A hybrid hierarchical learning framework is proposed to achieve high-precision assembly of 170mm cylindrical components with tolerance of 0.1mm. The low

safetyarxiv-cs-ro

LASSNet: Level-Aware Availability-Conditioned Spatial-Semantic Fusion for Brain Tumor Segmentation with Missing MRI Modalities

arXiv:2609.06733v1 Announce Type: new Abstract: Brain tumor segmentation from multimodal MRI relies on complementary evidence across four imaging sequences, yet one or more modalities may be unavailab

Latent-MoE: Domain-Aware Mixture-of-Experts for PDEs with Multi-Regime Physics

arXiv:2609.07814v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) struggle on PDEs whose governing physics varies across the domain. We trace this to a structural property of st

Layer Selection in VLMs for Zero-Shot OOD Detection via Multi-Resolution Entropy Estimation

arXiv:2609.08524v1 Announce Type: new Abstract: Out-of-distribution (OOD) detection is crucial for safe deployment of medical AI systems, where domain shifts arise across institutions, acquisition pro

Layer-Wise Gate-Controlled Prompt Truncation in a Multimodal Chest X-Ray Classifier

arXiv:2609.06590v1 Announce Type: cross Abstract: Mixture of Prompt Experts (MoPE) adapts multimodal transformers through input-dependent prompt composition, while retaining a fixed prompt length. We

Tutorials

Learning Metamaterial Eigenmodes with Wavelet-Encoded Fourier Neural Operators

arXiv:2609.08102v1 Announce Type: new Abstract: Machine learning surrogates based on neural operators have shown broad applicability in solving forward PDE problems. However, eigenvalue problems, in w

tutorialsarxiv-cs-lg

Learning to Price and Stock Under Contextual and Censored Demand

arXiv:2609.06083v1 Announce Type: new Abstract: To make optimal joint pricing and inventory control decisions is a critical challenge for modern retailers. In practice, retailers face changing market

Leveraging Cardiac Imaging to Improve ECG-Based Detection of Chagas Disease in Resource-Constrained Settings

arXiv:2609.08582v1 Announce Type: new Abstract: Chagas disease is a major cause of cardiomyopathy in Latin America. Cardiac magnetic resonance (CMR) imaging can characterize its structural abnormaliti

Leveraging contextual events on structure-aware next activity prediction

arXiv:2609.08622v1 Announce Type: new Abstract: Predictive process monitoring aims at forecasting various aspects of running processes. Among the different tasks, next activity prediction represents t

applicationsarxiv-cs-lg

Lightbits set to release KV cache engine to boost GPU performance

Lightbits Labs Ltd. today announced the general availability of Inferra, a software engine designed to improve the economics and performance of artificial intelligence inference by moving key-value ca

hardwaresiliconangle

Localized Visual Feature Aggregation via Focus Pooling for Visuomotor Policies

arXiv:2609.08408v1 Announce Type: new Abstract: Focusing on spatially localized, control-relevant visual cues has been shown to improve data efficiency in visuomotor policies by reducing the need to m

MAC-I^2: Learned Metrics-Aware Covariance for Robust Visual-Inertial Fusion in Initialization and Calibration

arXiv:2609.07116v1 Announce Type: new Abstract: Visual-Inertial (VI) fusion is fundamental to accurate and robust state estimation, where camera and IMU measurements are combined according to their re

MamMA: A Mamba-Based Pedestrian Trajectory Prediction Algorithm Considering Occupancy Map and Pedestrian Awareness States

arXiv:2609.08041v1 Announce Type: new Abstract: Many pedestrian trajectory prediction algorithms have been proposed to improve the safety of navigation for mobile robots working in human-robot coexist

local-aiarxiv-cs-cv

Industry

Man told ChatGPT he was feeling delusional. ChatGPT insisted he was Jesus.

In July 2026, a man with bipolar disorder named Michael Lines sued OpenAI after several months of conversations with ChatGPT that allegedly spurred a religious delusion in which he began believing he

industryars-technica

Map the Possibilities: Spatial Belief Fields for Language-Goal Aerial Navigation

arXiv:2609.05841v1 Announce Type: new Abstract: Language-goal aerial navigation requires an agent to local- ize a potentially unobserved target from relational instruc- tions and partial observations,

local-aiarxiv-cs-cv

MCANet: A Multi-Scale Class-Specific Attention Network for Multi-Label Post-Hurricane Damage Assessment Using UAV Imagery

arXiv:2509.04757v2 Announce Type: replace Abstract: Hurricanes cause widespread damage to buildings, roads, and other infrastructure, making timely post-disaster damage assessment critical for emergen

MedGSSR: Generalizable Medical Image Super-Resolution 3D Reconstruction via Hierarchical Feed-forward Gaussian Splatting

arXiv:2609.06874v1 Announce Type: cross Abstract: High-resolution volumetric medical imaging is critical for clinical diagnosis, yet acquisition is often limited by scanner hardware, scan time, and fo

local-aiarxiv-cs-cv

MGD: Moment Guided Diffusion for Maximum Entropy Generation

arXiv:2602.17211v2 Announce Type: replace-cross Abstract: Generating samples from limited information is a fundamental problem across scientific domains. Classical maximum entropy methods provide prin

MILAAP: Mobile Link Allocation via Attention-based Prediction

arXiv:2506.19947v2 Announce Type: replace-cross Abstract: Channel hopping (CS) communication systems must adapt to interference changes in the wireless network and to node mobility for maintaining thr

Mind-to-Face: Neural-Driven Photorealistic Avatar Synthesis via EEG Decoding

arXiv:2512.04313v2 Announce Type: replace Abstract: Current expressive avatar systems rely heavily on visual cues, failing when faces are occluded or when emotions remain internal. We present Mind-to-

mjorbit: A Simulation Framework for Space Robotics

arXiv:2609.08010v1 Announce Type: new Abstract: This paper presents a general framework for simulating multi-body space robots with contact. We bring efficient, large-scale robot simulation to in-spac

hardwarearxiv-cs-ro

Moment-Matching Probabilistic Data Association for Optimization-Based SLAM

arXiv:2609.05941v1 Announce Type: new Abstract: Optimization-based simultaneous localization and mapping (SLAM) makes it possible to reduce accumulated navigation errors of sensing platforms by return

Monocular Visual Odometry without Calibration or Test-time Optimization

arXiv:2510.03348v4 Announce Type: replace Abstract: The most accurate monocular visual odometry systems require known camera intrinsics, refine their estimates with test-time optimization, and recover

safetyarxiv-cs-cv

MRI-Guided Reslice-Refined Cross-Slice SDF Reconstruction of the Left Ventricle from Cardiac MRI with Sparse Axial Supervision

arXiv:2609.08148v1 Announce Type: new Abstract: Reconstructing a three-dimensional left-ventricular (LV) endocardial surface from cardiac magnetic resonance (CMR) data is challenging when supervision

safetyarxiv-cs-cv

MSSP: Multi-Scale Spatially-Constrained Partition for Unsupervised Semantic Segmentation of 3D Point Clouds

arXiv:2609.06959v1 Announce Type: new Abstract: 3D point cloud semantic segmentation is essential for real-world spatial understanding, yet the prohibitive cost of human annotations motivates unsuperv

applicationsarxiv-cs-cv

Multi-robot Learning-based Informative Path Planning Using Spatio-Temporal Gaussian Process Kalman Filter

arXiv:2609.05515v1 Announce Type: new Abstract: Multi-robot informative path planning (IPP) for persistent target monitoring requires robots to reason about spatial uncertainty, temporal evolution, an

safetyarxiv-cs-ro

Multi-Task Learning with Covariate-Overlap Regularization

arXiv:2505.24281v2 Announce Type: replace-cross Abstract: Multi-task learning improves data efficiency by sharing information across related tasks, but indiscriminate sharing can be harmful when their

safetyarxiv-cs-lg

Nearly Tight Rademacher Bounds for Sparsely Activated Neural Networks

arXiv:2609.09130v1 Announce Type: new Abstract: An input may activate few hidden units even when different inputs collectively use an entire network. We study the statistical complexity of this input-

safetyarxiv-cs-lg

Non-Coherent Over-the-Air Federated Learning: Protocol, Convergence, and Device Scheduling

arXiv:2609.08312v1 Announce Type: cross Abstract: To mitigate the scalability bottleneck in the radio access network (RAN) in federated edge learning (FEEL), over-the-air federated learning (AirFL) ex

safetyarxiv-cs-lg

On the Effectiveness of the z-Transform Method in Quadratic Optimization

arXiv:2507.03404v3 Announce Type: replace Abstract: The z-transform of a sequence is a classical tool used within signal processing, control theory, computer science, and electrical engineering. It al

Agents

Online Surrogate Repair: Decoupling High-Fidelity Feedback from Search Length in Closed-Loop Discovery

arXiv:2609.07655v1 Announce Type: new Abstract: Closed-loop AI scientists can generate candidate designs at low marginal computational cost, whereas reliable feedback may require wet-lab synthesis, ch

agentsarxiv-cs-lg

OpenAI’s rogue AI agents reached at least 12 more websites, researchers say https://fortune.com/2026/09/09/openai-rogue-ai-agents-reached-12…

Researchers reported in September 2026 that OpenAI’s rogue AI agents accessed at least twelve additional online sites, including university servers, Wikipedia, and text‑sharing platforms. These sites

safetygary-marcus--x

Ostrich: Taking Large Strides Through Stiff Contact in Differentiable Dynamics

arXiv:2609.08800v1 Announce Type: cross Abstract: Three properties determine whether a differentiable simulator can drive gradient-based optimization through contact: simulation accuracy, gradient rel

hardwarearxiv-cs-lg

PAI-Actor: Cinematic Multi-Character Replacement in Dynamic Scenes

arXiv:2609.05918v1 Announce Type: new Abstract: We present PAI-Actor, a cinematic multi-character animation framework for character replacement in dynamic movie scenes. Unlike conventional animation s

applicationsarxiv-cs-cv

PASTEL: Panoramic Alignment for Monocular 4D Scene Reconstruction

arXiv:2609.06099v1 Announce Type: new Abstract: Reconstructing 4D scenes from casually captured monocular video is vital for applications in virtual reality (VR) and embodied AI. Recent advances in 4D

safetyarxiv-cs-cv

PCSDiff: Diffusion-Based Bias Correction and Super Resolution Toward Practical Operational Medium-Term Precipitation Forecast

arXiv:2609.06942v1 Announce Type: new Abstract: Medium-range precipitation forecasts are impaired by persistent systematic biases, lead-time-dependent error accumulation, and coarse spatial resolution

local-aiarxiv-cs-lg

Agents

Phase-and-First-Arrival VLM Feedback for Sparse-Reward Reinforcement Learning in Surgical Manipulation

arXiv:2609.07211v1 Announce Type: new Abstract: Sparse outcome feedback limits what robots can learn from unsuccessful attempts at complex manipulation. Failed multi-stage surgical attempts can contai

agentsarxiv-cs-ro

Physics-Informed Neural Networks for Depth-Averaged Granular Avalanche Dynamics on Curved Topography

arXiv:2609.05542v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) provide a mesh-free framework for solving governing equations, but their application to granular avalanche dy

PlayTrain: An Efficient Reinforcement Learning Framework for LLM-Generated Adaptable JavaScript Games

arXiv:2609.09059v1 Announce Type: new Abstract: While many video-game environments (VGEs) have played crucial roles in advancing reinforcement learning (RL), developing novel VGEs or modifying existin

hardwarearxiv-cs-lg