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RSAJEV: Training-Free Abstaining Prototype Memory for Eliminating Silent Hallucination in JEV-Based Remote Sensing Classification

arXiv:2610.15742v1 Announce Type: new Abstract: Scene classification of remote sensing imagery with multimodal large language models (MLLMs) is formulated as a single-forward-pass decision problem: ca

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Human DGX agent

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RSIgen: Reciprocal Self-Improvement for Agentic Visual Generation

DGX agent

arXiv:2610.18688v1 Announce Type: new Abstract: Agentic visual generation produces experience that can improve the native understanding (agent) and generation roles of a unified multimodal backbone, b

model-releasesarxiv-cs-cv

14 Oct 2026

RT-J: Large-Scale Pretraining of Relational Transformers for Context-Efficient Predictions

arXiv:2610.17867v1 Announce Type: new Abstract: Foundation models for tables and relational databases are increasingly used for predictive tasks across various scientific and industrial domains. Howev

RTISSLAM: In-air Imaging Sonar SLAM using a Robust Pose Graph and Occupancy Grid Mapping

arXiv:2610.18479v1 Announce Type: new Abstract: Sonar was one of the first sensors with which mobile robots built maps, and in-air sonar keeps working where cameras and lidar fail, in darkness, smoke,

researcharxiv-cs-ro

S^3-PnP: Plug-and-Play Denoising for Scientific Imaging with Self-Supervised Score Priors

arXiv:2610.18458v1 Announce Type: new Abstract: Modern image restoration methods increasingly rely on large-scale supervised training, yet clean targets are often prohibitively difficult to obtain in

SAFE-KV: Causal Suffix Repair for Behavior-Preserving Non-Prefix KV Cache Reuse in RAG

arXiv:2610.15186v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) reuses the same documents across many requests, making non-prefix KV-cache reuse attractive. Yet a cached documen

Safety-Critical Quadrotor Navigation Using Fourth-Order Control Barrier Functions with Full Nonlinear Quadrotor Dynamics

arXiv:2610.14522v1 Announce Type: new Abstract: Safety-critical quadrotor navigation in cluttered environments typically relies on hierarchical architectures in which a high-level safety filter modifi

safetyarxiv-cs-ro

Safety-Oriented Trajectory Ranking from BEV Perception Outputs

arXiv:2610.14066v1 Announce Type: cross Abstract: Bird's-Eye-View (BEV) representations are increasingly used as compact inputs for autonomous driving perception and planning. However, lightweight and

Saliency-Guided Replay for Continual Learning in Deep Spiking Neural Networks

arXiv:2610.17998v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) are promising for energy-efficient neuromorphic computing, but they still suffer from catastrophic forgetting when lear

Same Function, Different Trajectory: No Standard Optimizer Is Equivariant to Transformer Reparameterization

arXiv:2610.18085v1 Announce Type: new Abstract: We show that two Transformers representing the same function can follow different training trajectories. For example, doubling a query matrix and halvin

Same Goal, Different Words: Spatial Instruction Sensitivity in World-Action Models

arXiv:2610.16242v1 Announce Type: new Abstract: World-action models should preserve the intended manipulation across equivalent descriptions of a spatial goal. We evaluate this consistency in 864 roll

researcharxiv-cs-ro

Sample-Optimal Multi-Group Learning with an ERM Oracle

arXiv:2610.15916v1 Announce Type: new Abstract: In multi-group learning, a single predictor must perform nearly as well as the best hypothesis in a class on every group in a rich, possibly infinite an

Sample-Size Extrapolation in Simulation-Based Inference via Statistical Scaling

arXiv:2610.16820v1 Announce Type: cross Abstract: In simulation-based inference (SBI), neural posterior estimators trained on a bounded range of sample sizes can become inaccurate on larger datasets b

Tutorials

Sampling from multimodal distributions with warm starts: Non-asymptotic bounds for the Reweighted Annealed Leap-Point Sampler

arXiv:2512.17977v2 Announce Type: replace-cross Abstract: Sampling from multimodal distributions is a central challenge in Bayesian inference and machine learning. In light of hardness results for sam

tutorialsarxiv-cs-lg

Sampling from Neural Operator Priors to Solve Partial Differential Equations

arXiv:2610.16396v1 Announce Type: new Abstract: Guided sampling with sparse observations and PDE residuals has recently been combined with neural operator priors to solve partial differential equation

Sanzaru: Benchmarking Protocol Formation under Epistemic & Communication Asymmetry

arXiv:2610.15163v1 Announce Type: cross Abstract: A language model's ability to solve a task individually does not ensure that a team can solve it under unequal access to information and communication

SARATHI: Decoupled Data-Free Probing and Adaptive Reconstruction for Structured LLM Pruning

arXiv:2610.15514v1 Announce Type: new Abstract: Structured pruning reduces the inference cost of large language models (LLMs) by permanently removing neurons and weight rows, yielding dense, hardware-

safetyarxiv-cs-lg

SarcasTraps: Effect of Sarcasm on Turkish Hate Speech Detection

arXiv:2610.16957v1 Announce Type: cross Abstract: Standard hate speech detection datasets often emphasize explicit harmful language, but directed harm can also be expressed indirectly, without clearly

Local Ai

Satellite-Free Training for Drone-View Geo-Localization

arXiv:2604.01581v4 Announce Type: replace Abstract: Drone-view geo-localization (DVGL) typically assumes access to satellite imagery during task-specific development. We study a late-arriving-gallery

local-aiarxiv-cs-cv

Scalable Identification of Physics-Based and Neural Dynamics from Partial Measurements

arXiv:2610.16559v1 Announce Type: cross Abstract: We present a scalable method for identifying nonlinear dynamics from partial measurements, supporting physics-based, neural-network, and gray-box mode

Scalable Multi-Human Cooperative Manipulation via Commander-Executor Coordination

arXiv:2610.14911v1 Announce Type: cross Abstract: Multi-human cooperative object manipulation is a highly challenging topic in humanoid control. While existing methods can handle simple collaborative

Scalable Power Sampling: Unlocking Efficient, Training-Free Reasoning for LLMs via Distribution Sharpening

arXiv:2601.21590v2 Announce Type: replace Abstract: Reinforcement learning (RL) post-training is a dominant approach for improving the reasoning performance of large language models (LLMs), yet growin

Agents

Scalable Weak-to-Strong Verifier Hardening for Agent Environments

arXiv:2610.15924v1 Announce Type: cross Abstract: Agent environments are essential for large language model (LLM) development. They use programmatic verifiers to turn complex outcomes into rewards. Ve

agentsarxiv-cs-lg

Scale-specific auxiliary multi-task contrastive learning for deep liver vessel segmentation

arXiv:2409.12333v2 Announce Type: replace-cross Abstract: Extracting hepatic vessels from abdominal images is of high interest for clinicians since it allows to divide the liver into functionally-inde

Scaling Latent Motor Adaptation to Coordinated Bimanual Manipulation

arXiv:2610.14833v1 Announce Type: new Abstract: Robust manipulation under uncertain object dynamics and geometry remains a core challenge in real-world robotics. Policies trained under fixed assumptio

safetyarxiv-cs-ro

Scaling Laws for Multimodal Data Mixtures

arXiv:2610.14423v1 Announce Type: cross Abstract: Frontier AI systems are increasingly natively multimodal, jointly pretrained on multiple modalities, such as text, vision, and audio. However, the sci

Scaling Online Optimal Transport Minibatches for Flow Matching

arXiv:2610.18838v1 Announce Type: cross Abstract: A central challenge in scaling flow models is maintaining stability in training and integration. In flow matching, this stability depends critically o

Hardware

Scaling Repeated-Data Pretraining: Batch Size, Regularization, and GPU-Time Tradeoffs

arXiv:2610.15965v1 Announce Type: new Abstract: We study pretraining when compute is abundant but unique training data are finite, requiring repeated training on the same data. We first revisit infini

hardwarearxiv-cs-lg

Tutorials

Scaling Unified Multimodal Models to Long-Horizon Interleaved Generation

arXiv:2610.17080v1 Announce Type: new Abstract: Unified multimodal models (UMMs) provide an interface for interleaved text-image generation, where generated visual states can directly inform subsequen

tutorialsarxiv-cs-cv

Scaling Vision Transformers Without Training: Prune-and-Merge Token Compression

arXiv:2610.18039v1 Announce Type: new Abstract: Vision Transformers achieve strong performance but incur high computational costs from quadratic token interactions. Training-free token reduction metho

ScalLoc: Continuous Oblique Thermal UAV Geo-Localization with a 2D Satellite Map

arXiv:2610.14866v1 Announce Type: new Abstract: Cross-modal Thermal Geo-localization (TG) provides an illumination-robust positioning solution for Unmanned Aerial Vehicles (UAVs) in Global Navigation

SceneForesee: Learning Scene Evolution for Spatiotemporal Reasoning

model-releasesarxiv-cs-cv

arXiv:2610.14439v1 Announce Type: new Abstract: Large multimodal models (LMMs) need to understand how entities move and interact as a scene develops. This requires following the same entities over tim

ScenePercept: Scenario-Conditioned Perceptual Assessment of Real-World User-Generated Content Images

model-releasesarxiv-cs-cv

arXiv:2610.17661v1 Announce Type: new Abstract: The rapid development of mobile imaging and social platforms has led to explosive growth in user-generated content images, making their systematic and c

ScenePlacer: Reformulating Scene-Level Object Pose Estimation as Visibility Field Learning

arXiv:2610.15734v1 Announce Type: new Abstract: We present ScenePlacer, a framework for scene-level pose estimation of objects generated by state-of-the-art native shape generation models, placing gen

Scenes as an Attack Surface: Uncovering Scene-Grounded Safety Failures in MLLMs

arXiv:2610.14094v1 Announce Type: new Abstract: Existing jailbreak attacks have exposed serious safety weaknesses in multimodal large language models (MLLMs). Most prior attacks rely on specially cons

Tutorials

SchemaPose: RGB-Based Category-Level Pose Estimation with Parametric Category Schema

arXiv:2610.18374v1 Announce Type: new Abstract: RGB-based category-level 9D pose estimation remains highly challenging because a monocular system must generalize across unseen object instances while j

tutorialsarxiv-cs-cv

scHFBiMamba: a bidirectional Mamba autoencoder for cardiac disease-state classification from single-nucleus RNA-seq data

arXiv:2610.15117v1 Announce Type: new Abstract: To evaluate whether a compact bidirectional state-space autoencoder improves joint classification of species, cell type, and disease state from single-n

ScienceBuddy-PV: A Verifier-Governed Recursive Improvement Protocol for Panvascular Intervention Research

arXiv:2610.14523v1 Announce Type: cross Abstract: ScienceBuddy-PV adapts the ScienceBuddy recursive-in-recursive design to panvascular intervention research through a structured evidence ledger, devic

SCOPE Before You Sample: Conformal Scores Guide Posterior Exploration for Fast and Calibrated Bayesian Predictive Inference

arXiv:2610.17146v1 Announce Type: cross Abstract: Bayesian predictive regions account for parameter uncertainty but can be poorly calibrated under model misspecification, even with expensive full MCMC

Screening Collapse under Recursive Synthetic Data

arXiv:2610.15617v1 Announce Type: cross Abstract: Recursive synthetic-data training can degrade a fitted model, but its effects on the variable-screening stage that precedes model fitting are less und

Sea-Net: A Small and Inherently Interpretable Neural Network for Time Series Classification

arXiv:2610.17939v1 Announce Type: cross Abstract: Traditional time-series classification methods often operate as black boxes, providing a class prediction without indicating which time point or time

SEAR: Self-Evolving Agentic Robotics

model-releasesarxiv-cs-ro

arXiv:2610.18792v1 Announce Type: new Abstract: Frontier language-model agents can now improve robots on their own: they write control code, test it, and keep what works as skills and memories for the

Searching for What Matters: Open-Ended Discovery of Multiple Hypotheses with Agentic Data Exploration

arXiv:2610.17874v1 Announce Type: new Abstract: Discovering what drives an outcome from data is central to science and often requires deciding what is worth investigating before a specific hypothesis

Agents

SEEK: Agentic Knowledge Graph Retrieval for Secure Code Generation

arXiv:2610.14968v1 Announce Type: cross Abstract: Large Language Models (LLMs) can generate functionally correct code while introducing exploitable security weaknesses, particularly when developers sp

agentsarxiv-cs-lg

Local Ai

Seg2Click: Learning Pixel-Level Action Masks for GUI Visual Grounding

arXiv:2610.16234v1 Announce Type: new Abstract: Visual grounding is a central challenge for GUI agents, requiring an instruction to be mapped to a target within a crowded screenshot. Coordinate genera

local-aiarxiv-cs-cv

Local Ai

Segment Where You Look: Attention as the Interface Between Language Models and Segmenters

arXiv:2610.18729v1 Announce Type: new Abstract: Vision-language models (VLMs) that segment from language must pass the location of the referent to a pixel decoder. The dominant interface compresses it

local-aiarxiv-cs-cv

Selective Inference for Clustering Under Unknown Covariance

arXiv:2610.17458v1 Announce Type: cross Abstract: Unsupervised clustering is widely used to discover underlying group structure, after which researchers often seek to validate these groups via post-ho

Selective Successor Eligibility Traces for RLVR

arXiv:2605.05965v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become a key approach for improving the reasoning abilities of large language models. Howe

safetyarxiv-cs-lg