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SpatialBlock: Enhancing Spatial Intelligence in LVLMs via Synthetic Block-Stacking Problem

arXiv:2609.07064v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) have achieved strong performance on diverse visual tasks, yet their ability to reconstruct and reason about the 3D

applicationsarxiv-cs-cv

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Spatiotemporal Heterogeneity of AI-Driven Traffic Flow Patterns and Land Use Interaction: A GeoAI-Based Analysis of Multimodal Urban Mobility

DGX agent

arXiv:2603.05581v2 Announce Type: replace Abstract: Urban traffic flow is governed by the complex, nonlinear interaction between land use configuration and spatiotemporally heterogeneous mobility dema

safetyarxiv-cs-lg

9 Sept 2026

Spectral Prioritized Sweeping in Nonstationary Reinforcement Learning

arXiv:2609.06186v1 Announce Type: new Abstract: Prioritized Sweeping (PS) accelerates model-based reinforcement learning by selecting backups according to Bellman residual magnitude. In nonstationary

Speed Limit for Information Acquisition in Stochastic Learning Dynamics

arXiv:2609.08219v1 Announce Type: cross Abstract: Neural networks acquire internal representations through learning. In this work, we formulate stochastic gradient descent (SGD) as a Markovian stochas

SphereSOD: Geometry-Structure Coupled Learning for 360 Salient Object Detection

arXiv:2609.07571v1 Announce Type: new Abstract: 360{eg} salient object detection (SOD) aims to accurately segment salient regions across a full field of view. However, equirectangular projection (ERP)

Spheriverse: 3D Scene Understanding from Spherical Observations in the Wild

arXiv:2609.09012v1 Announce Type: new Abstract: Spherical observations provide global visual context for 3D scene understanding. However, visual information is encoded in an angular domain, whereas th

SPOT: Spatial Perception-Oriented Long-Horizon Humanoid Teleoperation

arXiv:2609.07933v1 Announce Type: new Abstract: High-quality demonstration data is becoming a central bottleneck for training general-purpose humanoid robots. While recent humanoid teleoperation syste

safetyarxiv-cs-ro

SQS: Bayesian DNN Compression through Sparse Quantized Sub-distributions

arXiv:2510.08999v2 Announce Type: replace Abstract: Compressing large-scale neural networks is essential for deploying models on resource-constrained devices. Most existing methods adopt weight prunin

Squeeze10-LLM: Squeezing LLMs' Weights by 10 Times via a Staged Mixed-Precision Quantization Method

arXiv:2507.18073v2 Announce Type: replace Abstract: Deploying large language models (LLMs) is challenging due to their massive parameters and high computational costs. Ultra low-bit quantization can s

SRAW-Attack: Space-Reweighted Adversarial Warping Attack for SAR Target Recognition

arXiv:2601.10324v3 Announce Type: replace Abstract: Synthetic aperture radar (SAR) imagery exhibits intrinsic information sparsity due to its unique electromagnetic scattering mechanism. Despite the w

Srijika: OpenType-Layout-Reusing Font Restyling for Nine Indic Scripts

arXiv:2609.05661v1 Announce Type: new Abstract: We present Srijika, a system for producing installable OpenType fonts for nine Brahmic scripts: Devanagari, Tamil, Bengali, Telugu, Kannada, Malayalam,

Stability and Generalization of Straight-Through Estimators for Training Two-Layer Quantized Neural Networks

arXiv:2609.06430v1 Announce Type: new Abstract: We study the identity straight-through estimator (STE) for training a two-layer binary-activation network with hinge loss from the perspective of Statis

Stable-MM-R1: Anchoring Multimodal Reasoning Dynamics via Entropy-Guided Stratification

arXiv:2609.07148v1 Announce Type: cross Abstract: While Reinforcement Learning (RL) effectively incentivizes reasoning in Large Language Models, current pipelines are hindered by training instability

safetyarxiv-cs-cv

STAR-Pro: Stage-Wise Token Adaptive Reduction with Progressive Refinement for Efficient Large Vision-Language Models

arXiv:2609.05916v1 Announce Type: new Abstract: Large vision-language models (LVLMs) achieve strong multimodal understanding, but the hundreds to thousands of visual tokens they process impose substan

State-of-the-Art in Learning-by-Demonstration with Passive Observation for Industrial Assembly Automation

arXiv:2609.07165v1 Announce Type: new Abstract: Learning-by-Demonstration (LbD) enables intuitive robot programming by capturing expert skills, which is crucial for agility in high-mix, low- volume ma

applicationsarxiv-cs-ro

Statistical versus machine learning-based spatial interpolation of post-processed ensemble weather forecasts

arXiv:2609.07512v1 Announce Type: new Abstract: Statistical post-processing improves ensemble weather forecasts, but generating calibrated predictions at locations without observations remains challen

Steering Geometry: Validating Human Value Geometry in LLM Steering Space

arXiv:2609.06289v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed in alignment-sensitive contexts, activation steering has emerged as a lightweight, inference

Steering Interference Reflects the Model's Defaults, Not the Behavior Directions

arXiv:2609.06951v1 Announce Type: new Abstract: Activation steering promises modular control of language model behavior: a behavior such as politeness corresponds to a direction in a model's activatio

Steering Under Compression: Dose-Response, Capability Cost, and Failure Asymmetry in Quantized LLMs

arXiv:2609.06473v1 Announce Type: new Abstract: Inference-time activation steering enables behavioral control of large language models without parameter modification, while post-training quantization

Stochastic Nonconvex Bilevel Optimization: Improved Rates Without Rare-Visit Assumption

arXiv:2609.06580v1 Announce Type: cross Abstract: We investigate stochastic simple bilevel optimization with smooth and possibly nonconvex upper- and lower-level objectives. Existing stochastic extens

Stochastically Perturbed Weights: Ensembles from Deterministic Machine-Learning Weather Models

arXiv:2609.08412v1 Announce Type: new Abstract: Machine-learning weather models (MLWMs) now match or outperform operational numerical weather prediction (NWP) at global medium-range forecasting, at fa

applicationsarxiv-cs-lg

STP-BENCH: A Unified Systematic Benchmark for Virtual Spatial Transcriptomics from Histopathology Images

arXiv:2609.05956v1 Announce Type: new Abstract: Spatial transcriptomics (ST) provides unprecedented insights into tumor heterogeneity by capturing spatially resolved gene expression, yet its high expe

Strategic Doctrine Language Models (sdLM): A Learning-System Framework for Doctrinal Consistency and Geopolitical Forecasting

arXiv:2601.14862v2 Announce Type: replace Abstract: We introduce Strategic Doctrine Language Models (sdLM), a learning-system framework for multi-document strategic reasoning with doctrinal consistenc

Streaming Hierarchical Inference with Tabular Foundation Models

arXiv:2609.07956v1 Announce Type: new Abstract: Tabular Foundation Models (TFMs) have recently demonstrated strong predictive performance through in-context learning, but their deployment in high-thro

Structural Entropy-Driven Graph Diffusion Generation for One-Shot Federated Graph Learning

arXiv:2609.06499v1 Announce Type: new Abstract: One-shot federated graph learning (FGL) requires the server to estimate client contributions from highly compressed information, yet conventional volume

Structurally Close, Temporally Distant: Measuring Security Exposure in Long-Horizon LLM Agents

arXiv:2609.05911v1 Announce Type: cross Abstract: Long-horizon LLM agents interact with untrusted content, persistent memory, external state, and sensitive tools. Existing analyses often characterize

Local Ai

Structured Extrema Errors in Classical Surrogates for Viscous Burgers: A Physics-Consistent Interpretation

arXiv:2609.07952v1 Announce Type: new Abstract: We study the local errors of classical machine-learning surrogate models, which approximate the time evolution of the one-dimensional viscous Burgers eq

local-aiarxiv-cs-lg

STSG-VQA: Evidence-Grounded Temporal Question Answering from Surgical Spatio-Temporal Scene Graphs

arXiv:2609.08543v1 Announce Type: new Abstract: Despite recent advances in surgical vision-language models (VLMs), temporal reasoning remains limited because existing supervision is largely frame-cent

Studying Image Tokenizers as Visual Languages in Unified Multimodal Models

arXiv:2609.09143v1 Announce Type: new Abstract: Image tokenizers define the ``visual language'' of unified multimodal models, yet are commonly studied through isolated metrics or generation-/understan

Suan: Rectifying Direct Preference Safety Alignment in Large Language Models

arXiv:2609.08634v1 Announce Type: new Abstract: Integrating robust safety guardrails into Large Language Models (LLMs) is essential for delivering helpful yet harmless responses. While proprietary sys

Sub-6 GHz Over-the-Air AMC via Curriculum Fine-Tuned CNN-Transformers

arXiv:2609.07726v1 Announce Type: cross Abstract: Automatic modulation classification (AMC) models are frequently trained and validated on synthetic or channel-cabled data, leaving open the question o

Sub-Pixel Affine Registration of Space Debris Images via the Radon Point Spread Function

arXiv:2609.06929v1 Announce Type: new Abstract: Inter-frame affine misalignment caused by platform jitter and attitude adjustments poses a fundamental challenge for multi-frame analysis of point targe

Subject-Relative Micro-Motion and Sleep Dynamics for Near-Infrared Video Sleep Staging

arXiv:2609.05550v1 Announce Type: new Abstract: Near-infrared (NIR) video is a promising modality for contactless sleep monitoring, but recent video-based sleep staging methods often use it as a route

Subspace Optimization for Backpropagation-Free Continual Test-Time Adaptation

arXiv:2603.28678v2 Announce Type: replace Abstract: We introduce PACE, a backpropagation-free continual test-time adaptation system that directly optimizes the affine parameters of normalization layer

SUN: Reaching for Novelty in Reinforcement Learning

arXiv:2609.08642v1 Announce Type: new Abstract: Exploration in reinforcement learning (RL) remains a fundamental challenge. Recent goal-conditioned RL strategies (which select goals to encourage broad

Supervised Cross-Modal Feature Alignment for Zero-Wearable Freezing of Gait Detection in Parkinsonism

arXiv:2609.08317v1 Announce Type: new Abstract: Objective assessment of Freezing of Gait (FoG) in Parkinson's disease (PD) relies predominantly on wearable Inertial Measurement Units (IMUs). While IMU

safetyarxiv-cs-cv

SupGRPO: Enhancing GRPO with Matching-based Online SFT for Text Spotting

arXiv:2609.07081v1 Announce Type: new Abstract: Text spotting requires both accurate text recognition and precise spatial localization. Current specialised spotters excel at predicting tight bounding

Support Topology and Gradient Mixing in Sinkhorn Layers

arXiv:2609.07954v1 Announce Type: cross Abstract: Sparse Sinkhorn layers use a fixed support graph to restrict transport between tokens. How does this graph control gradient propagation through the sc

Sustained Performance and Energy Accounting for Nonlinear Forecasting Across Classical and Simulated Quantum Models

arXiv:2510.25183v2 Announce Type: replace-cross Abstract: Energy-efficient AI should be evaluated across the full application pipeline, not only by lowest error or shortest training time. We study thi

SWE-Tester: Training Open-Source LLMs for Issue Reproduction in Real-World Repositories

arXiv:2601.13713v2 Announce Type: replace-cross Abstract: Software testing is crucial for ensuring the correctness and reliability of software systems. Automated generation of issue reproduction tests

applicationsarxiv-cs-lg

SwiftExplorer: Training-free Diffusion Model Alignment with Swift Diversity Exploration

arXiv:2609.06651v1 Announce Type: new Abstract: Diffusion models have general generative abilities but struggle to align with specific objectives. Fine-tuning can improve alignment, yet its training c

SyncWorld: Visual Calibration Enables World Models as Zero-Shot Simulators

arXiv:2609.09155v1 Announce Type: new Abstract: World models are increasingly used as policy-in-the-loop imagination environments, where reliable rollouts require fine-grained controllability with res

safetyarxiv-cs-cv

Synergistic Fusion of Topological Structure and Temporal Semantics of Mobility for Urban Region Embedding

arXiv:2609.08268v1 Announce Type: new Abstract: Urban region embeddings have shown promising results in diverse urban sensing tasks such as crime, income, and service-call prediction. Recent methods i

Synthesizability Prediction of Crystalline Structures with Structure-Aware Feature Learning and Uncertainty Quantification

arXiv:2510.19251v2 Announce Type: replace-cross Abstract: Predicting which hypothetical inorganic crystals can be experimentally realized remains a central challenge in accelerating materials discover

SynthGait-19K: A Physically Grounded Synthetic Video Dataset for Gait Parameter Estimation

arXiv:2609.08108v1 Announce Type: new Abstract: Accurate estimation of clinically meaningful gait parameters from monocular video is important for scalable mobility assessment, yet progress is limited

SynthRCT: Scalable Conditional Deformation Synthesis for Synthetic Repeat CT Generation

arXiv:2609.08627v1 Announce Type: new Abstract: In proton therapy, plans are typically optimized on a single planning CT, making robustness evaluation essential under anatomical changes. However, curr

TabBench-Bio: A Living Benchmark for Machine Learning on High-Dimensional Biomedical Tables

arXiv:2609.07441v1 Announce Type: new Abstract: Biomedical tables often combine thousands of measured variables with only tens or hundreds of labelled samples, a regime that is poorly represented in g

TacClip: a clip-on sensor measures dynamic contact forces without covering the fingerpads

arXiv:2609.08214v1 Announce Type: new Abstract: TacClip is a minimally encumbering wearable device for recording fingertip deformation caused by contact forces and vibrations. It can be combined with

researcharxiv-cs-ro