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SimCortex v2: Joint Cortical Surface Reconstruction with Near-Zero Collisions and Self-Intersections

model-releasesarxiv-cs-cv

arXiv:2610.07378v1 Announce Type: new Abstract: Reconstructing cortical WM and pial surfaces from structural magnetic resonance imaging (MRI) is a prerequisite for surface-based neuroanatomical analys

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Human DGX agent

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SimToolReal: An Object-Centric Policy for Zero-Shot Dexterous Tool Manipulation

DGX agent

arXiv:2602.16863v3 Announce Type: replace-cross Abstract: The ability to manipulate tools significantly expands the set of tasks a robot can perform. Yet, tool manipulation represents a challenging cl

safetyarxiv-cs-ai

7 Oct 2026

Singular Value Decomposition: A Geometric Rediscovery, Where Proofs Become Algorithms

arXiv:2610.08565v1 Announce Type: new Abstract: This article is a geometric rediscovery of the singular value decomposition, with a further claim: the construction it builds is the machinery behind mu

Sinkhorn doubly stochastic attention rank decay analysis

arXiv:2604.07925v2 Announce Type: replace-cross Abstract: The self-attention mechanism is central to the success of Transformer architectures. However, standard row-stochastic attention has been shown

SkillFormer: Skill-Decomposed Adaptation for Audio Language Models

arXiv:2610.07533v1 Announce Type: cross Abstract: Audio language models must handle dozens of distinct skills, from pitch comparison and speaker counting to musical tempo estimation and emotion recogn

Skillful Data-Driven Subseasonal Soil Moisture Forecasting: Prospects and Limits for Flash Drought Prediction

arXiv:2610.07060v1 Announce Type: new Abstract: Despite substantial progress in short-to-medium-range weather forecasting, predicting high-impact events such as flash droughts remains a key challenge

SkillPoison: Progressive Skill Poisoning via Successful Experiences

arXiv:2610.07645v1 Announce Type: cross Abstract: Self-improving LLM agents increasingly distill successful experiences into persistent, reusable skills. Existing skill attack methods corrupt this lea

Small Language Models for Smart Data Model Classification at the Edge: A Cost-Aware Hybrid Approach

arXiv:2610.07093v1 Announce Type: new Abstract: The rapid proliferation of heterogeneous data sources within the Internet of Things (IoT) across domains such as smart cities, energy management, and en

Smart Content Ingestion for Generative AI Workloads

arXiv:2610.07091v1 Announce Type: new Abstract: The evolution of machine learning has progressively changed where intelligence resides in an AI system. In conventional machine learning the task, data

agentsarxiv-cs-ai

SMART: Zero-Shot Sim-to-Real Articulated Object Manipulation via Large-Scale Synthetic Pretraining

arXiv:2610.07652v1 Announce Type: cross Abstract: The ability to interact with articulated objects is essential for embodied intelligent systems, but collecting large-scale real-world demonstrations f

agentsarxiv-cs-ai

SoloQ: Calibration-Free Quantization for Diffusion Language Models

arXiv:2610.07121v1 Announce Type: new Abstract: Diffusion large language models dLLMs) have emerged as a promising alternative to autoregressive language models through bidirectional diffusion-based t

Tutorials

Source-Learned Reliance for Selective Test-Time Adaptation of Multimodal Time Series

arXiv:2610.07499v1 Announce Type: new Abstract: Multimodal wearable systems must remain reliable when sensor streams become noisy or unavailable. Existing multimodal test-time adaptation (TTA) methods

tutorialsarxiv-cs-lg

Sparse2comm: Towards Robust Cooperative 3D Object Detection

arXiv:2610.08573v1 Announce Type: new Abstract: Cooperative perception improves autonomous driving by sharing complementary observations among vehicles and roadside infrastructure for 3D object detect

safetyarxiv-cs-cv

SpaTime: Streaming Vision-Language Models for Spatio-temporal Reasoning

arXiv:2610.08713v1 Announce Type: new Abstract: Embodied agents must reason about 3D space while the video is still arriving, answering questions as soon as they have observed enough of the scene. VLM

researcharxiv-cs-cv

Speak to a Protein: An Interactive Multimodal Co-Scientist

arXiv:2510.17826v2 Announce Type: replace-cross Abstract: Building a working mental model of a protein typically requires weeks of reading, cross-referencing crystal and predicted structures, and insp

SPEAR: Five Principles for Interactive Human-Agent Alignment

arXiv:2610.07204v1 Announce Type: cross Abstract: Recent AI alignment work often frames alignment as a pre-deployment optimization problem: collect human feedback, learn preferences or principles, fin

safetyarxiv-cs-ai

SpecBraM: What Should an EEG Foundation Model Predict? Masked Band-Power Prediction versus Waveform Reconstruction

arXiv:2610.07484v1 Announce Type: new Abstract: Self-supervised EEG models often reconstruct masked waveforms or predict discrete codes. We study a task-aligned alternative: masked band-power predicti

Spectra: Exact Component Transport for Test-Time Prior Adaptation in Simulation-Based Inference

arXiv:2610.08021v1 Announce Type: new Abstract: Simulation-based inference (SBI) has become a powerful approach to Bayesian inference in complex scientific models whose likelihoods are difficult or im

SPECTRUM: Proximal Spectral Modulation for Looped Self-Distillation

arXiv:2610.07237v1 Announce Type: new Abstract: A model that learns from its own outputs inherits more than their correctness: it inherits which solutions it produces. We formulate Looped Self-Distill

SpeedrunBench: Challenging LLM Agents with Video Game Speedrunning

arXiv:2610.08076v1 Announce Type: new Abstract: Frontier LLM agents have been shown to be capable of solving increasingly complex tasks for which humans have measurable solutions. This begs the pertin

SquidAgent: Parallelize Wisely, Coordinate Efficiently

arXiv:2610.08647v1 Announce Type: new Abstract: LLM-based agents solve complex multi-step tasks, but sequential execution incurs substantial latency. In principle, parallelizing work across multiple a

SSR: Sparse Segment Reduction for Ternary GEMM Acceleration

arXiv:2610.08403v1 Announce Type: new Abstract: Large Language Models (LLMs) require substantial computational resources, limiting their deployment on resource-constrained hardware. Ternary LLMs mitig

ST-Bench: A Spatial-Temporal Benchmark for Multi-Agent System Generation on Scientific Research Tasks

arXiv:2610.07763v1 Announce Type: new Abstract: The rapid progress of LLM-based multi-agent systems (MAS) has shown that they largely outperform single agents on coding, math, and QA tasks, where exec

Stability of Measure-to-Measure Transformers on Sub-Gaussian Data

arXiv:2610.07717v1 Announce Type: cross Abstract: Transformers have exhibited impressive empirical success across various domains, but their theoretical foundations remain less developed. This work co

Stabilizing language models under continual learning via condition-anchored distillation

model-releasesarxiv-cs-cl

arXiv:2610.06940v1 Announce Type: new Abstract: Continual adaptation of language models can change their output distribution on prompts learned earlier, while retaining every old prompt-answer pair ma

Stabilizing Off-Policy Training for Long-Horizon LLM Agent via Turn-Level Importance Sampling and Clipping-Triggered Normalization

arXiv:2511.20718v3 Announce Type: replace-cross Abstract: Reinforcement learning (RL) algorithms such as PPO and GRPO are widely used to train large language models (LLMs) for multi-turn agentic tasks

safetyarxiv-cs-ai

Stable Scores, Unstable Answers: Frame Phase and Option Order in Video Multiple-Choice Evaluation

arXiv:2610.08649v1 Announce Type: new Abstract: Video-language models are ranked by multiple-choice accuracy on frames from a uniform grid. The grid has two parameters, a rate and a phase, and benchma

researcharxiv-cs-cv

StaFIR: Convex Learning of Stationarity-Aware Causal Filters

arXiv:2610.07430v1 Announce Type: new Abstract: Reducing nonstationarity in a persistent time series entails deciding how much of its temporal dependence to remove. In finance, fractional differencing

Local Ai

StairVLA: Stage-Aware Hierarchical Action Generation for Vision-Language-Action Models

arXiv:2610.07756v1 Announce Type: new Abstract: Vision-language-action (VLA) models increasingly rely on diffusion- or flow-matching-based action heads to generate continuous robot actions. These acti

local-aiarxiv-cs-ro

State-Aware Interaction MIL for Rare Joint Molecular Phenotype Prediction in Colorectal Cancer and Lung Adenocarcinoma

arXiv:2610.06991v1 Announce Type: new Abstract: Joint molecular phenotype prediction is complicated by small joint-positive populations and overlapping histological features across alternative molecul

researcharxiv-cs-cv

Stateless Language Agents: Scaling Long-Horizon Automated Research

arXiv:2610.07625v1 Announce Type: cross Abstract: Automated research systems increasingly run LLM agents over long horizons, but more inference does not by itself produce more progress: agents replay

agentsarxiv-cs-ai

Statistical Turbulence and High-Fidelity Disturbance Fields for Quadrotor Flight Control

arXiv:2610.06874v1 Announce Type: cross Abstract: Reinforcement-learning quadrotor controllers are usually trained under simplified wind models, yet the impact of wind-field fidelity, as opposed to ma

safetyarxiv-cs-lg

Steering Diffusion Models to Rare Events with Sequential Monte Carlo

arXiv:2610.08652v1 Announce Type: cross Abstract: Diffusion models are increasingly used as surrogates for expensive simulators in weather prediction, molecular dynamics, and materials design. In thes

Local Ai

Stepped MoE: Segment-Level Routing with Configurable Inference Complexity

arXiv:2610.07348v1 Announce Type: cross Abstract: Training large language models (LLMs) is resource-intensive, and adapting them for diverse deployment scenarios with varying computational constraints

local-aiarxiv-cs-ai

Stochastic Gradient Descent Ascent is Suboptimal for Nonconvex-PL Min-Max Games

arXiv:2610.07814v1 Announce Type: cross Abstract: How far can stochastic gradient descent ascent (SGDA) go by tuning its timescale ratio and step sizes in nonconvex min-max games? We answer this quest

Tutorials

Stochastic Siamese MAE Pretraining for Longitudinal Medical Images

arXiv:2512.23441v2 Announce Type: replace-cross Abstract: Temporally aware image representations are crucial for capturing disease progression in 3D volumes of longitudinal medical datasets. However,

tutorialsarxiv-cs-cv

STOCK-JEPA: Prior-Anchored Latent Revision Representation Learning in Equity Markets

arXiv:2610.07006v1 Announce Type: new Abstract: Learning effective representations helps characterize the structure and dynamics of equity markets from financial data with a low signal-to-noise ratio.

STRUCTURALCOST: A controlled reading time dataset for modeling human sentence processing difficulty

arXiv:2610.08208v1 Announce Type: cross Abstract: We introduce STRUCTURALCOST, a self-paced reading dataset of 475 participants and 40,800 observations isolating the processing cost of long-distance s

Structure-Aware Graph Abstention for Reliable Selective Forecasting

arXiv:2610.08322v1 Announce Type: new Abstract: Selective forecasting abstains on high-risk test windows under a retained-coverage budget. Existing gates such as TEM (Brusokas et al., 2025) score each

safetyarxiv-cs-lg

Structure-aware Keypoint Localization for Videofluoroscopic Swallowing Study

arXiv:2610.07726v1 Announce Type: new Abstract: Videofluoroscopic Swallowing Study (VFSS) is one of the gold standard for diagnosing swallowing disorders, providing dynamic X-ray imaging of the swallo

safetyarxiv-cs-cv

Structure, Not Belief: Correlated Thompson Sampling from LLM-Derived Covariance in Combinatorial Semi-Bandits

arXiv:2610.07470v1 Announce Type: cross Abstract: Combinatorial Thompson sampling (CTS) draws independent posterior samples for every arm, so its exploration dynamics ignore any relation among arms. W

Structured but Silent: Probing Capability Requirements in LLM Hidden States

arXiv:2610.08018v1 Announce Type: new Abstract: Reliable tool use requires more than triggering a mechanism or matching a query to an API description. Before selecting a specific tool, an agent must f

agentsarxiv-cs-cl

Structuring MoE Expert Selection for Agentic Reinforcement Learning

arXiv:2610.07332v1 Announce Type: cross Abstract: Long-horizon LLM agents are frequently implemented using sparse mixture-of-experts (MoE) models, yet the co-design of agentic behavior and MoE structu

agentsarxiv-cs-cl

Supermarket Product Detection and Recognition: Utilizing Deep Learning with Rectified Imagery

arXiv:2610.08126v1 Announce Type: cross Abstract: Product Identification has sprung up to become one of the most challenging problems in the automation of the retail industry. With the new industry 5.

SURGE: Sonar-fUsed Reconstruction and localization via image-gated Graph Estimation

arXiv:2610.07472v1 Announce Type: new Abstract: Remotely operated vehicles (ROVs) are widely used to explore and inspect underwater environments such as caves, shipwrecks, and submerged infrastructure

researcharxiv-cs-ro

Surviving the Router: Optimizing Skill Injections for Retrieval and Execution

arXiv:2610.08098v1 Announce Type: cross Abstract: AI agents increasingly rely on modular third-party 'skills' that are dynamically selected by skill routers to execute complex tasks. While recent stud

SWAP: Stepwise Action Policy Routing for Vision-Language-Action Models

arXiv:2610.06926v1 Announce Type: new Abstract: Robot manipulation systems using Vision-Language-Action (VLA) model backbones typically use just one VLA for task execution. However, individual VLAs do

safetyarxiv-cs-ro

SWE-Game: Can Coding Agents Build the Games We Want?

arXiv:2609.33678v2 Announce Type: replace Abstract: We introduce SWE-Game, a benchmark of 247 tasks grounded in 41 executable reference Godot games spanning 13 gameplay categories in 2D and 3D. Five t