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Smoothness as a Constraint for Stable Humanoid Locomotion

arXiv:2609.24552v1 Announce Type: new Abstract: Embodied AI systems, particularly humanoid robots deployed in real world scenarios require whole-body control policies that are both task-responsive and

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Human DGX agent

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SocioVerse2: A Longitudinal Dynamic Social Simulation Framework under a Human-AI Co-evolutionary Paradigm

DGX agent

arXiv:2609.24911v1 Announce Type: new Abstract: Social simulation offers the social sciences an experimental instrument that the real world cannot supply, and generative agents have transformed it by

model-releasesarxiv-cs-cl

22 Sept 2026

SoK: Formal Methods for Fact-Checking and Information Integrity

arXiv:2609.23239v1 Announce Type: new Abstract: An automated fact-checking system returns a label: the claim is true, or it is false. In many such systems the verdict remains the primary output. What

researcharxiv-cs-cl

SolarFlowRefiner: Refinement-Aware Flow Matching for Surface Solar Radiation Downscaling

arXiv:2609.22126v1 Announce Type: cross Abstract: High-resolution surface solar radiation (SSR) is important for solar forecasting and grid operation. However, physically consistent reanalysis product

SomaNet: Weakly Supervised Learning for Instance Soma Segmentation in 3D Electron Microscopy with Partial Annotations

arXiv:2609.23019v1 Announce Type: cross Abstract: Soma instance segmentation, i.e., identifying and delineating individual cell somas as distinct instances, is crucial for cellular analysis and connec

Some Dialects Are More Equal Than Others: Non-Prestigious Arabic Dialectal Bias in LLMs

arXiv:2609.23955v1 Announce Type: new Abstract: Previous work on Egyptian Arabic in NLP has focused largely on the prestigious Cairene Egyptian Arabic (CEA) dialect, resulting in a lack of representat

safetyarxiv-cs-cl

SPACE: Semantic Projection and Alignment of CLIP Embeddings for Domain Adaptation

arXiv:2609.23248v1 Announce Type: new Abstract: A fundamental challenge in deploying vision models is domain shift, which arises when training and test data follow different distributions, leading to

safetyarxiv-cs-cv

SparkDiffusion: Mitigating the High-Sparsity Trap --- A Unified Framework for up to 265imes Single-GPU Acceleration of Visual Generation

arXiv:2609.23153v1 Announce Type: new Abstract: Video diffusion transformers are expensive because attention dominates long spatiotemporal token sequences. We identify the high-sparsity trap: at extre

local-aiarxiv-cs-cv

Sparse Regression Distilled from a Single Robust Fit

arXiv:2609.23937v1 Announce Type: cross Abstract: Robust linear fits can resist response contamination yet remain too dense or unstable for useful global explanations. We propose penalized distillatio

Hardware

SPARSER: Sparse Variable Projection by Exploiting Separable Structure in Robotic Perception

arXiv:2609.24708v1 Announce Type: new Abstract: Robotic perception often requires solving large nonlinear least-squares (NLS) problems. While sparsity has been widely exploited to scale solvers, a com

hardwarearxiv-cs-ro

Agents

Spatial Action Review: A Visual Analytics Dashboard for Auditing Language-to-Action Hand-offs in Electron Microscopy

arXiv:2609.24470v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly explored as interfaces for scientific image analysis, where a visual question-answering (VQA)

agentsarxiv-cs-cv

Spatial-Interactor: Learning Spatial Reasoning through Interaction with the Observable Physical World

arXiv:2609.23038v1 Announce Type: cross Abstract: Spatial reasoning is essential for vision-language models (VLMs) to understand and act in the physical world. Reasoning in dynamic environments requir

local-aiarxiv-cs-lg

Spatiotemporal Flux Probing for Single-Photon Videography

arXiv:2609.22479v1 Announce Type: new Abstract: We address the problem of recovering high-speed videos from dynamic scenes under extreme photon sparsity. Existing methods rely on aggregating photon de

SPeaR: Test-Time Adaptation with Steering Primitives for Realigning Representations

arXiv:2609.24111v1 Announce Type: cross Abstract: Test-time adaptation (TTA) addresses distribution shift using only unlabeled test data. Existing methods typically adapt pretrained models by updating

Hardware

Spectral Rendering Without a Spectral Renderer: Learned Spectral Codes for RGB Pipelines

arXiv:2602.18741v3 Announce Type: replace-cross Abstract: Spectral rendering reproduces the wavelength-dependent appearance that RGB rendering cannot: metamerism, colour shifts under spectrally rich i

hardwarearxiv-cs-cv

Speech-to-SOAP: End-to-End Summarization of Medical Dialogues: KIT@BeTraC 2026

arXiv:2608.24327v2 Announce Type: replace Abstract: With the advent of Large Language Models and its instruction following capabilities a promising application is the task of summarization. Within thi

researcharxiv-cs-cl

SPHQuant: Efficient extreme low bit weight quantization for Vision-Language Models

arXiv:2609.24875v1 Announce Type: new Abstract: Recent foundation models are moving toward native multimodal Vision-Language Models (VLMs), making VLMs a central form of next-generation foundation mod

SPIBER: Reconstructing Free Energy Landscapes from Short, Unconverged Trajectories with Generative Flow Networks

arXiv:2609.22663v1 Announce Type: cross Abstract: Molecular systems have many degrees of freedom, but their metastable behavior can often be described by a few collective variables. Identifying these

SPID: Distilled Protein Backbone Generation

arXiv:2510.03095v4 Announce Type: replace Abstract: Diffusion- and flow-based generative models have recently demonstrated strong performance in protein backbone generation tasks, offering unprecedent

applicationsarxiv-cs-lg

Spiking Neural Network Actor-Critic Proximal Policy Optimization Control for Autonomous UAV Navigation Through Constrained Openings in Civil Infrastructure and Buildings

arXiv:2609.23643v1 Announce Type: new Abstract: Autonomous navigation of unmanned aerial vehicles in constrained three-dimensional environments has been a challenge in the robotics domain. The applica

Splat-CBF: Safe Next-Best-View Control in 3D Gaussian-Splat Maps

arXiv:2609.23100v1 Announce Type: new Abstract: Where to look and how to move? A robot navigating an unmapped environment must do both at once, and the two goals pull against each other. The regions m

SRPR-Net: Semantic and Relational Prompt Refinement for Automated SAM-based Instance Segmentation

arXiv:2609.24226v1 Announce Type: new Abstract: Instance segmentation is a fundamental computer vision task with diverse real-world applications. Recently, prompt-driven foundation models have shown p

applicationsarxiv-cs-cv

SSP-GNN: Learning to Track via Bilevel Optimization

arXiv:2407.04308v4 Announce Type: replace Abstract: We propose a graph-based tracking formulation for multi-object tracking (MOT) where target detections contain kinematic information and re-identific

ST-Topo GAN: A Motor EEG-to-EMG Decoding Model Matched to Wrist Movement Complexity

arXiv:2609.22128v1 Announce Type: cross Abstract: The wrist plays a critical role in upper-limb function by enabling precise hand positioning, force regulation, and object manipulation. Continuous bra

STA-TFM: Spatio-Temporal Aggregation Across Views TransForMer for Pose Estimation

arXiv:2609.24482v1 Announce Type: new Abstract: Monocular 3D human pose estimation (HPE) remains challenging due to depth ambiguity, occlu- sions, and the need for temporal consistency. While multi-vi

Stability-Aligned Residual Adaptation for Rapid Recovery from Dynamics Shifts

arXiv:2603.07775v2 Announce Type: replace Abstract: Robotic systems deployed beyond controlled environments encounter abrupt and unobserved dynamics shifts that induce substantial transient performanc

local-aiarxiv-cs-ro

Stability and Bifurcation Analysis of Nonlinear PDEs via Random Projection-based PINNs: A Krylov-Arnoldi Approach

arXiv:2603.21568v2 Announce Type: replace-cross Abstract: We present a numerical framework for the stability and bifurcation analysis of nonlinear partial differential equations (PDEs) in which the so

Stable and Efficient Real-World Online VLA Post-Training via Asynchronous Replay-Anchored Policy Improvement

arXiv:2609.22888v1 Announce Type: new Abstract: Online post-training of vision-language-action (VLA) models requires efficient use of robot interaction and reliable policy improvement from continually

Stagewise Anomaly Detection for E-Transaxle Quality Monitoring Using Wavelet and STFT Features

arXiv:2609.22172v1 Announce Type: cross Abstract: This paper presents two interpretable machine-learning frameworks for quality screening of e-transaxle assemblies in electric vehicles: a Stagewise Wa

applicationsarxiv-cs-lg

STAR: Scene- and Task-Aware 4D Radar Preprocessing Towards End-to-End Cognitive Radar

arXiv:2609.24151v1 Announce Type: new Abstract: Four-dimensional (4D) Radar has emerged as a key sensor for environmental perception, providing range, azimuth, elevation, and Doppler measurements whil

StateMem: Single-State Residual Memory with Adaptive Inference for Vision-Language-Action Policies

arXiv:2609.22684v1 Announce Type: cross Abstract: Memory-dependent robotic manipulation often requires later actions to use information from earlier interactions. Existing vision-language-action (VLA)

applicationsarxiv-cs-lg

Tutorials

StationPDE: Station-Oriented Surface PDE Learning for Multi-Station Multivariate Weather Forecasting

arXiv:2609.22123v1 Announce Type: new Abstract: Multi-station multivariate weather forecasting aims to forecast future weather variables at multiple weather stations from historical surface observatio

tutorialsarxiv-cs-lg

Statistical Convergence of Transformer Encoder-Accelerated Robust Reinforcement Learning

arXiv:2609.23775v1 Announce Type: new Abstract: Obtaining the optimal action-value function in Markov decision processes is computationally intensive in large state--action spaces. In this study, we p

Statistical Inference for Adversarial Training: Central Limit Theorems via Optimal Transport

arXiv:2609.22240v1 Announce Type: new Abstract: The purpose of this paper is to rigorously quantify the statistical and learning-theoretic properties of adversarial training models for classification.

Stealing profits: Spread-based temporal hierarchy forecasting for day-ahead electricity markets

arXiv:2609.23223v1 Announce Type: cross Abstract: Day-ahead electricity price forecasts support trading and storage decisions, but for battery arbitrage predicting intraday price spreads is more relev

Steerable and Reactive Grasping Through Modular Design with a Three-Point Interface

arXiv:2609.24896v1 Announce Type: new Abstract: Dexterous grasping requires deciding where to grasp, reaching the target, and maintaining stable contact. We connect these stages through a compact thre

local-aiarxiv-cs-ro

Steering Through Contact: A Finite-Support Motion Model for Single-Track Center-Articulated Robots

arXiv:2609.23271v1 Announce Type: new Abstract: Trajectory planning and control in field robotics rely on predicting how propulsion and steering affect vehicle motion when contact points undergo slip.

applicationsarxiv-cs-ro

Steering Vector Fields for Context-Aware Inference-Time Control in Large Language Models

arXiv:2602.01654v2 Announce Type: replace Abstract: Steering vectors (SVs) offer a lightweight way to control large language models (LLMs) at inference time by shifting hidden activations, providing a

local-aiarxiv-cs-cl

StenoVLA-3D: 3D-Aware Reasoning VLA for Navigation Through Gastrointestinal Stenoses

arXiv:2609.24187v1 Announce Type: cross Abstract: Autonomous endoscopic navigation requires the policy model to predict actions from texture-poor monocular observations, make safe control decisions, a

safetyarxiv-cs-cv

Agents

StepKV: Step-Aware KV Cache Compression for LLM Agents

arXiv:2609.22158v1 Announce Type: new Abstract: Key-value (KV) caching is essential for efficient autoregressive large language model (LLM) inference, but the cache grows linearly with context length,

agentsarxiv-cs-lg

STEVE: Stabilizing Textual Gradient-Based Prompt Optimization via Error-Driven Refinement and Regularized Verification

model-releasesarxiv-cs-cl

arXiv:2609.23716v1 Announce Type: new Abstract: Textual-gradient methods automate prompt optimization through natural-language feedback, but their iterative updates can be unstable. We identify two so

Stochastic Flow Map for Count Data

arXiv:2609.23290v1 Announce Type: cross Abstract: High-dimensional count data are common in scientific applications, but most diffusion and flow models are designed for continuous or categorical data,

local-aiarxiv-cs-lg

Stochastic Reconfiguration as Statistical Filtering for Overparameterized Neural Quantum States

model-releasesarxiv-cs-lg

arXiv:2609.23334v1 Announce Type: cross Abstract: Stochastic reconfiguration (SR) is the standard optimizer for neural quantum states (NQS), but modern NQS often have far more parameters than Monte Ca

STOP: Structured On-Policy Pruning of Long-Form Reasoning in Low-Data Regimes

model-releasesarxiv-cs-cl

arXiv:2605.13165v2 Announce Type: replace Abstract: Long chain-of-thought (Long CoT) reasoning improves performance on multi-step problems, but it also induces overthinking. This inefficiency is espec

Strategic Classification Has a Missing Lever: Audit Risk

arXiv:2609.22534v1 Announce Type: cross Abstract: Strategic classification studies how a decision maker should choose a classifier when the agents being classified can adjust their features in respons

safetyarxiv-cs-lg

Agents

Strategy Accumulation and Guided Execution for Automated LLM Fine-Tuning

arXiv:2609.22257v1 Announce Type: cross Abstract: Producing task-specific large language models requires discovering effective training strategies through experimentation. Automated fine-tuning system

agentsarxiv-cs-cl

Streaming Deep Reinforcement Learning Finally Works

model-releasesarxiv-cs-lg

arXiv:2410.14606v3 Announce Type: replace Abstract: Learning from a stream of experience as it arrives, also known as streaming learning, is a core part of natural learning. However, reliable streamin

Hardware

Streaming Video Editing with Easy Adaptation

arXiv:2609.24788v1 Announce Type: new Abstract: In this paper, we propose SVEET, a framework that requires merely training on a pretrained bidirectional video diffusion model but supports high-quality

hardwarearxiv-cs-cv