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Sim-to-Real Aware End-to-End Learning Environment for Micromobility

arXiv:2609.28969v1 Announce Type: new Abstract: While end-to-end autonomous driving systems show promise, their application to micromobility vehicles is hindered by simulators failing to capture speci

safetyarxiv-cs-ro

Human

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Simple Torque-Observation Alignment for Zero-Shot Sim-to-Real Grasping with a Direct-Drive Gripper

DGX agent

arXiv:2609.29031v1 Announce Type: new Abstract: Torque observations in reinforcement learning remain challenging because simulated and measured torque differ in scale, offset, and noise. In this paper

safetyarxiv-cs-ro

25 Sept 2026

Singularity Analysis for the Perspective-Four and Five-Line Problems

arXiv:2609.29417v1 Announce Type: new Abstract: This paper deals with image-based visual servoing and pose estimation by observing four and five lines. Our main interest is to determine the relative c

researcharxiv-cs-ro

SkinAgent AI: A Safety-Grounded Multimodal Agentic Framework for Non-Diagnostic Skincare Support

arXiv:2609.29341v1 Announce Type: new Abstract: Consumer-facing skincare AI must coordinate visual evidence, product information, tool use, and user-facing actions within explicit evidence and safety

SLCA-GRPO: Resolving Cross-Segment Credit Misattribution in Tool-Calling RL

arXiv:2609.29050v1 Announce Type: new Abstract: Tool-calling agents produce heterogeneous outputs, interleaving structured tool invocations with user-facing natural language summaries. This output het

safetyarxiv-cs-ai

Small yet Assistive: Spatially-Aware Post-Training for Low Vision

model-releasesarxiv-cs-cl

arXiv:2609.28757v1 Announce Type: cross Abstract: An estimated 1 billion people worldwide live with vision impairment, yet current vision-language models (VLMs) produce descriptions too vague for safe

Smartphone-Based Method for Automated Speed Enforcement

arXiv:2609.30107v1 Announce Type: new Abstract: Smartphone cameras and computer vision (CV) hold significant promise in assisting public agencies with enforcing traffic laws and enhancing road safety.

safetyarxiv-cs-cv

SMILESGNN: Interpretable Clinical Toxicity Prediction via SMILES-Graph Cross-Attention Fusion

arXiv:2609.28553v1 Announce Type: cross Abstract: Drug toxicity prediction is critical for reducing late-stage attrition in drug discovery, yet remains challenging due to severe class imbalance, scaff

researcharxiv-cs-ai

Agents

Sources: OpenAI found ~24 incidents of its agents acting in undesirable ways as of mid-September; OpenAI says its agents leaked 53 images from ChatGPT users (Reuters)

Reuters: Sources: OpenAI found ~24 incidents of its agents acting in undesirable ways as of mid-September; OpenAI says its agents leaked 53 images from ChatGPT users — Two months after OpenAI disclose

agentstechmeme

Spaceborne differential photogrammetry for control-free measurement of large-gradient deformation with structural immunity and a predictable accuracy envelope

arXiv:2609.29550v1 Announce Type: new Abstract: Optical satellite image correlation measures wide-area deformation in regimes where coherent interferometric synthetic aperture radar fails because disp

safetyarxiv-cs-cv

Industry

SpaceX has introduced a new website for its AI training clusters in Tennessee/Mississippi. New info: • Tesla Megapacks will provide 3.3 GWh …

SpaceX has introduced a new website for its AI training clusters in Tennessee/Mississippi. New info: • Tesla Megapacks will provide 3.3 GWh to Colossus 2, enough to power Memphis for two hours, making

industryelon-musk--x

Industry

SpaceX's supercomputing facilities in the Mid-South rank among the world’s most advanced AI training clusters, spanning over 2.5 million fee…

SpaceX's supercomputing facilities in the Mid-South rank among the world’s most advanced AI training clusters, spanning over 2.5 million feet, millions of GPUs, and over two gigawatts of compute → htt

industryelon-musk--x

SPADE-DFL: Communication-Efficient Decentralized Federated Learning via Derivative-Free Linearized ADMM

arXiv:2609.29446v1 Announce Type: new Abstract: Reducing communication in derivative-free decentralized learning requires controlling the disagreement accumulated over multiple local updates. This pap

SpaFactor: Lightweight Spatial Context-Aware Gene Program Modeling for Histology-to-Transcriptomics Inference

arXiv:2609.28563v1 Announce Type: new Abstract: Spatial transcriptomics (ST) profiles gene expression within tissue architecture, but its cost and experimental complexity limit routine use. Predicting

SPARQL-LLM: Real-Time SPARQL Query Generation from Natural Language Questions

arXiv:2512.14277v2 Announce Type: replace-cross Abstract: The advent of large language models is contributing to the emergence of novel approaches that promise to better tackle the challenge of genera

Spatio-temporally complementary feature propagation on graphs for longitudinal AADT estimation

arXiv:2609.29906v1 Announce Type: new Abstract: The estimation of Annual Average Daily Traffic (AADT) is vital for transportation planning and infrastructure maintenance, yet obtaining accurate values

applicationsarxiv-cs-lg

Spectral Amplitude Purification in Distribution Matching for Diffusion Distillation

arXiv:2609.29116v1 Announce Type: new Abstract: Distribution Matching Distillation (DMD) enables high-quality diffusion sampling in only a few steps, but its optimization dynamics remain dominated by

researcharxiv-cs-cv

Spectral Graph Neural Networks with Hermite Polynomials: A Comprehensive Study

arXiv:2609.28979v1 Announce Type: new Abstract: We study spectral graph neural networks built from Hermite polynomials and propose HermNet, a simple model that combines a nodewise predictor with norma

safetyarxiv-cs-lg

Spectral-Guided Diffusion: Accelerating Inference via Static Spectral Layer Scheduling

arXiv:2609.29505v1 Announce Type: new Abstract: Diffusion inference repeatedly evaluates the same large network. We ask whether pretrained weights alone can identify residual branches that need not be

SpectralCTGaussians: Projection-Domain Reconstruction and Basis Material Decomposition for Spectral CT using 3D Gaussian Splatting

arXiv:2609.29638v1 Announce Type: new Abstract: Spectral computed tomography (CT) extends conventional CT by measuring attenuation across multiple energy channels, allowing improved modeling of physic

applicationsarxiv-cs-cv

Speculative Evaluation of Stochastic LLMs

arXiv:2609.28560v1 Announce Type: cross Abstract: Evaluating a stochastic large language model is costly: benchmark scores estimate expected performance from randomized rollouts, yet uniform repetitio

Spent the last two months seeing how far a non programmer (me) can get building a proper game with nothing but ChatGPT in a browser.

Gonna ironically preface this with: I haven't written the text below with an LLM. boxxy.io So I thought I'd show you what I've made over the last couple of months, because for me this has probably bee

model-releasesr-chatgpt

Local Ai

Splash on a 40-core M5 Max: +20% decode by tuning the kernels for your own chip

FYI the engine's default kernel rules were measured on smaller chips (16/20-core M5s and a 32-core M4 Max), so a 40-core M5 Max runs guesses. Splash's repo includes a developer tool, “make tune-kernel

local-air-localllama

Tutorials

SplatLabel: Pseudo-Labelling through 4D Gaussian Splatting

arXiv:2609.29836v1 Announce Type: new Abstract: While 2D Vision Foundation Models offer a pathway to automate 3D semantic pseudo-labelling, translating these priors into robust 3D representations typi

tutorialsarxiv-cs-cv

Spooftral: Can Voxtral Audio-Language Model Detect Speech Spoofing?

arXiv:2609.28713v1 Announce Type: cross Abstract: Self-supervised learning (SSL) countermeasures (CMs) have shown strong performance in recent years. However, they often show degraded performance whil

researcharxiv-cs-cl

Spot on. 'When we got attacked, our team initially turned to frontier closed-source APIs that blocked us because of safeguards that still ca…

Spot on. 'When we got attacked, our team initially turned to frontier closed-source APIs that blocked us because of safeguards that still can’t always tell the difference between attackers and defende

safetyclem-delangue--x

Spot, Separate, and Enhance: Fully Generative Approach for Audio Mixing

arXiv:2609.29169v1 Announce Type: cross Abstract: We introduce Spot, Separate, and Enhance (SSE), the first multimodal, user-guided generative model for audio remixing and enhancement. SSE enhances vi

Stable and Faithful Explanations for Knowledge Tracing

arXiv:2609.28502v1 Announce Type: new Abstract: Knowledge tracing (KT) models predict student performance opaquely, limiting pedagogical action. This study contributes a validation protocol testing pr

Stacked SVD or SVD stacked? A Random Matrix Theory perspective on data integration

arXiv:2507.22170v2 Announce Type: replace-cross Abstract: Modern data analysis increasingly requires identifying shared latent structure across multiple high-dimensional datasets. A commonly used mode

safetyarxiv-cs-lg

Stale Does Not Mean Unsafe: Guard Precision for Tool-Using LLM Agents under Infrastructure State Races

arXiv:2609.29522v1 Announce Type: new Abstract: Tool-using language-model agents increasingly mutate schedulers, data pipelines, object stores, and access-control systems. Between an agent's read and

StepCOPS: Closed-Testing Lower-Tail Certificates for Language-Model Policy Selection

model-releasesarxiv-cs-cl

arXiv:2609.29549v1 Announce Type: new Abstract: Post-training pipelines must select one language-model policy from many checkpoints, prompts, and decoding rules. Mean evaluator scores can conceal rare

Stochastic Inertial Krasnosel'skii-Mann Iteration Achieves Near-Optimal Sample Complexity

model-releasesarxiv-cs-lg

arXiv:2609.28543v1 Announce Type: cross Abstract: We analyze a simple stochastic inertial Krasnosel'skii--Mann (iKM) method for finding a fixed point of a nonexpansive operator in a real Hilbert space

Agents

Stochastic Semantic Evidence Graphs: Uncertainty Propagation and Governance for Agentic AI

arXiv:2609.29703v1 Announce Type: new Abstract: AI-agent evaluations usually inspect a final answer, yet error may enter through evidence, retrieval, prompting, generation or decision mapping. We intr

agentsarxiv-cs-cl

Storage Intelligence advisor: Know what changed in your storage estate and act on it

The volume of data being generated today brings both opportunity and massive operational complexity. Most teams that operate at scale don't discover issues until they appear on an invoice — and by the

safetygoogle-cloud-ai

STRAND: Benchmarking and Improving Object-Centric Spatio-Temporal Monitoring in Video Large Language Models

model-releasesarxiv-cs-cl

arXiv:2609.29607v1 Announce Type: cross Abstract: While multimodal large language models (MLLMs) have advanced video understanding, they remain highly prone to hallucinations in dynamic scenes. We arg

Stream Recursion Model (SRM)

model-releasesarxiv-cs-lg

arXiv:2609.28809v1 Announce Type: new Abstract: Mechanistic interpretability seeks to make verifiable statements about the internal behavior of large language models (LLMs). Many interpretability tech

Tutorials

Streaming-WAM: Action-Conditioned World-Action Model for Asynchronous Robot Manipulation

arXiv:2609.28927v1 Announce Type: new Abstract: World action models (WAMs) that use future visual prediction at inference time incur substantial generation costs. Asynchronous execution reduces waitin

tutorialsarxiv-cs-ro

Structured Pose-Conditioned Flow Matching for Generative 5G CSI Augmentation

arXiv:2609.29912v1 Announce Type: cross Abstract: With the growing demand for privacy-preserving and occlusion-resilient human pose recognition (HPR), 5G channel state information (CSI) offers a promi

applicationsarxiv-cs-ai

Style, Not Self: Surface Cues Explain Zero-Shot Code Attribution by Large Language Models

arXiv:2609.30048v1 Announce Type: new Abstract: If a language model can recognize code it wrote, it may favor that code as a judge, and instances of one model monitoring each other could collude. We t

Sufficiently Reduced Distributional Regression

arXiv:2609.29291v1 Announce Type: cross Abstract: We propose Sufficiently Reduced Distributional Regression (SRDR), a generative method that combines conditional distribution estimation with nonlinear

Industry

Super happy to release SmolDataEnvs: 5,000 verifiable RL environment tasks for hill-climbing small models in code and data science by @adith…

Super happy to release SmolDataEnvs: 5,000 verifiable RL environment tasks for hill-climbing small models in code and data science by @adithya_s_k 100% open source: environments, evals, training! http

industryclem-delangue--x

SWE-Prometheus: Measuring Engineering Governance Improvements in Real-World Repositories

arXiv:2609.29465v1 Announce Type: new Abstract: Large language model based coding agents have made substantial progress on repository-level software engineering tasks. Existing repository benchmarks,

Swift1.5-Qwen3.8-Flash-Next is phenomenal vs. base 3.8-Flash!

model-releasesr-localllama

TL;DR - Swift Flash is a killer model that massively reduces excess reasoning. Try it out! If you haven't seen from my previous comparison posts, I'm a huge fan of the Swift Qwen3.8 models. I've been

SwitchPFN: Shared Switching Dynamics for Frozen In-Context Time Series Classification

model-releasesarxiv-cs-lg

arXiv:2609.29814v1 Announce Type: new Abstract: Tabular foundation models (TFMs) provide a promising route to time-series classification, but their effectiveness depends on how sequential data are con

Synthetic Enclosed Echoes: A New Dataset to Mitigate the Gap Between Simulated and Real-World Sonar Data

arXiv:2505.15465v2 Announce Type: replace Abstract: This paper introduces Synthetic Enclosed Echoes (SEE), a novel dataset designed to enhance robot perception and 3D reconstruction capabilities in un

applicationsarxiv-cs-ro

Synthetic Hospital: An Open, Verifiable, Physician-Validated Longitudinal EHR Benchmark

arXiv:2609.30027v1 Announce Type: new Abstract: Frontier language models are rarely used in clinical workflows because the realistic, longitudinal benchmarks needed to develop them are scarce. Real el

System Identification of an Octocopter in Hover using Full-Harmonic Orthogonal Multisine Inputs

arXiv:2609.29832v1 Announce Type: cross Abstract: A new method for multi-input flight maneuver design for system identification is presented. The method consists of injecting 'full-harmonic' orthogona

researcharxiv-cs-ro

TabSieve: Explicit In-Table Evidence Selection for Tabular Prediction

arXiv:2602.11700v2 Announce Type: replace-cross Abstract: Tabular prediction can benefit from in-table rows as few-shot evidence, yet existing tabular models typically perform instance-wise inference