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Sensitivity-Positional Co-Localization in GQA Transformers

arXiv:2604.07766v1 Announce Type: new Abstract: We investigate a fundamental structural question in Grouped Query Attention (GQA) transformers: do the layers most sensitive to task correctness coincid

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Agents

SensorPersona: An LLM-Empowered System for Continual Persona Extraction from Longitudinal Mobile Sensor Streams

DGX agent

arXiv:2604.06204v1 Announce Type: cross Abstract: Personalization is essential for Large Language Model (LLM)-based agents to adapt to users' preferences and improve response quality and task performa

agentsarxiv-cs-ai

10 Apr 2026

SentinelSphere: Integrating AI-Powered Real-Time Threat Detection with Cybersecurity Awareness Training

arXiv:2604.06900v1 Announce Type: cross Abstract: The field of cybersecurity is confronted with two interrelated challenges: a worldwide deficit of qualified practitioners and ongoing human-factor wea

Local Ai

SepSeq: A Training-Free Framework for Long Numerical Sequence Processing in LLMs

arXiv:2604.07737v1 Announce Type: new Abstract: While transformer-based Large Language Models (LLMs) theoretically support massive context windows, they suffer from severe performance degradation when

local-aiarxiv-cs-cl

Severity-Aware Weighted Loss for Arabic Medical Text Generation

arXiv:2604.06346v1 Announce Type: cross Abstract: Large language models have shown strong potential for Arabic medical text generation; however, traditional fine-tuning objectives treat all medical ca

Local Ai

ShadowNPU: System and Algorithm Co-design for NPU-Centric On-Device LLM Inference

arXiv:2508.16703v4 Announce Type: replace-cross Abstract: On-device running Large Language Models (LLMs) is nowadays a critical enabler towards preserving user privacy. We observe that the attention o

local-aiarxiv-cs-ai

SHAPE: Stage-aware Hierarchical Advantage via Potential Estimation for LLM Reasoning

arXiv:2604.06636v1 Announce Type: cross Abstract: Process supervision has emerged as a promising approach for enhancing LLM reasoning, yet existing methods fail to distinguish meaningful progress from

Shapes are not enough: CONSERVAttack and its use for finding vulnerabilities and uncertainties in machine learning applications

arXiv:2603.13970v2 Announce Type: replace Abstract: In High Energy Physics, as in many other fields of science, the application of machine learning techniques has been crucial in advancing our underst

Shortcut Learning in Glomerular AI: Adversarial Penalties Hurt, Entropy Helps

arXiv:2604.07936v1 Announce Type: new Abstract: Stain variability is a pervasive source of distribution shift and potential shortcut learning in renal pathology AI. We ask whether lupus nephritis glom

safetyarxiv-cs-cv

SIM1: Physics-Aligned Simulator as Zero-Shot Data Scaler in Deformable Worlds

arXiv:2604.08544v1 Announce Type: cross Abstract: Robotic manipulation with deformable objects represents a data-intensive regime in embodied learning, where shape, contact, and topology co-evolve in

safetyarxiv-cs-cv

Agents

SkillClaw: Let Skills Evolve Collectively with Agentic Evolver

arXiv:2604.08377v1 Announce Type: cross Abstract: Large language model (LLM) agents such as OpenClaw rely on reusable skills to perform complex tasks, yet these skills remain largely static after depl

agentsarxiv-cs-cl

SkillSieve: A Hierarchical Triage Framework for Detecting Malicious AI Agent Skills

arXiv:2604.06550v1 Announce Type: cross Abstract: OpenClaw's ClawHub marketplace hosts over 13,000 community-contributed agent skills, and between 13% and 26% of them contain security vulnerabilities

SkillTrojan: Backdoor Attacks on Skill-Based Agent Systems

arXiv:2604.06811v1 Announce Type: cross Abstract: Skill-based agent systems tackle complex tasks by composing reusable skills, improving modularity and scalability while introducing a largely unexamin

SL-FAC: A Communication-Efficient Split Learning Framework with Frequency-Aware Compression

arXiv:2604.07316v1 Announce Type: new Abstract: The growing complexity of neural networks hinders the deployment of distributed machine learning on resource-constrained devices. Split learning (SL) of

SleepNet and DreamNet: Enriching and Reconstructing Representations for Consolidated Visual Classification

arXiv:2409.01633v4 Announce Type: replace-cross Abstract: An effective integration of rich feature representations with robust classification mechanisms remains a key challenge in visual understanding

Small Vision-Language Models are Smart Compressors for Long Video Understanding

arXiv:2604.08120v1 Announce Type: cross Abstract: Adapting Multimodal Large Language Models (MLLMs) for hour-long videos is bottlenecked by context limits. Dense visual streams saturate token budgets

Smart Commander: A Hierarchical Reinforcement Learning Framework for Fleet-Level PHM Decision Optimization

arXiv:2604.07171v1 Announce Type: new Abstract: Decision-making in military aviation Prognostics and Health Management (PHM) faces significant challenges due to the 'curse of dimensionality' in large-

SMFD-UNet: Semantic Face Mask Is The Only Thing You Need To Deblur Faces

arXiv:2604.07477v1 Announce Type: new Abstract: For applications including facial identification, forensic analysis, photographic improvement, and medical imaging diagnostics, facial image deblurring

applicationsarxiv-cs-cv

Smoothing the Edges: Smooth Optimization for Sparse Regularization using Hadamard Overparametrization

arXiv:2307.03571v4 Announce Type: replace Abstract: We present a framework for smooth optimization of explicitly regularized objectives for (structured) sparsity. These non-smooth and possibly non-con

SMPL-GPTexture: Dual-View 3D Human Texture Estimation using Text-to-Image Generation Models

arXiv:2504.13378v2 Announce Type: replace-cross Abstract: Generating high-quality, photorealistic textures for 3D human avatars remains a fundamental yet challenging task in computer vision and multim

safetyarxiv-cs-cv

SMT-AD: a scalable quantum-inspired anomaly detection approach

arXiv:2604.06265v1 Announce Type: new Abstract: Quantum-inspired tensor networks algorithms have shown to be effective and efficient models for machine learning tasks, including anomaly detection. Her

Soft-Quantum Algorithms

arXiv:2604.06523v1 Announce Type: cross Abstract: Quantum operations on pure states can be fully represented by unitary matrices. Variational quantum circuits, also known as quantum neural networks, e

safetyarxiv-cs-ai

SOLAR: Communication-Efficient Model Adaptation via Subspace-Oriented Latent Adapter Reparametrization

arXiv:2604.08368v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning (PEFT) methods, such as LoRA, enable scalable adaptation of foundation models by injecting low-rank adapters. However,

SonoSelect: Efficient Ultrasound Perception via Active Probe Exploration

arXiv:2604.05933v3 Announce Type: replace Abstract: Ultrasound perception typically requires multiple scan views through probe movement to reduce diagnostic ambiguity, mitigate acoustic occlusions, an

researcharxiv-cs-cv

Local Ai

Space Filling Curves is All You Need: Communication-Avoiding Matrix Multiplication Made Simple

arXiv:2601.16294v2 Announce Type: replace-cross Abstract: General Matrix Multiplication (GEMM) is the cornerstone of HPC workloads and Deep Learning. State-of-the-art vendor libraries tune tensor layo

local-aiarxiv-cs-ai

Sparse-Aware Neural Networks for Nonlinear Functionals: Mitigating the Exponential Dependence on Dimension

arXiv:2604.06774v1 Announce Type: cross Abstract: Deep neural networks have emerged as powerful tools for learning operators defined over infinite-dimensional function spaces. However, existing theori

SpatialMosaic: A Multiview VLM Dataset for Partial Visibility

model-releasesarxiv-cs-cv

arXiv:2512.23365v3 Announce Type: replace Abstract: The rapid progress of Multimodal Large Language Models (MLLMs) has unlocked the potential for enhanced 3D scene understanding and spatial reasoning.

Spatio-Temporal Grounding of Large Language Models from Perception Streams

model-releasesarxiv-cs-ro

arXiv:2604.07592v1 Announce Type: new Abstract: Embodied-AI agents must reason about how objects move and interact in 3-D space over time, yet existing smaller frontier Large Language Models (LLMs) st

Spatiotemporal Gaussian representation-based dynamic reconstruction and motion estimation framework for time-resolved volumetric MR imaging (DREME-GSMR)

arXiv:2604.06482v1 Announce Type: cross Abstract: Time-resolved volumetric MR imaging that reconstructs a 3D MRI within sub-seconds to resolve deformable motion is essential for motion-adaptive radiot

SpecQuant: Spectral Decomposition and Adaptive Truncation for Ultra-Low-Bit LLMs Quantization

arXiv:2511.11663v2 Announce Type: replace-cross Abstract: The emergence of accurate open large language models (LLMs) has sparked a push for advanced quantization techniques to enable efficient deploy

Spectral Edge Dynamics Reveal Functional Modes of Learning

arXiv:2604.06256v1 Announce Type: cross Abstract: Training dynamics during grokking concentrate along a small number of dominant update directions -- the spectral edge -- which reliably distinguishes

SPICE: Submodular Penalized Information-Conflict Selection for Efficient Large Language Model Training

arXiv:2601.23155v2 Announce Type: replace-cross Abstract: Information-based data selection for instruction tuning is compelling: maximizing the log-determinant of the Fisher information yields a monot

Spike-based alignment learning solves the weight transport problem

arXiv:2503.02642v3 Announce Type: replace-cross Abstract: In both machine learning and in computational neuroscience, plasticity in functional neural networks is frequently expressed as gradient desce

safetyarxiv-cs-lg

Hardware

Splats under Pressure: Exploring Performance-Energy Trade-offs in Real-Time 3D Gaussian Splatting under Constrained GPU Budgets

arXiv:2604.07177v1 Announce Type: cross Abstract: We investigate the feasibility of real-time 3D Gaussian Splatting (3DGS) rasterisation on edge clients with varying Gaussian splat counts and GPU comp

hardwarearxiv-cs-lg

Splits! Flexible Sociocultural Linguistic Investigation at Scale

arXiv:2504.04640v3 Announce Type: replace Abstract: Variation in language use, shaped by speakers' sociocultural background and specific context of use, offers a rich lens into cultural perspectives,

researcharxiv-cs-cl

Squeeze Evolve: Unified Multi-Model Orchestration for Verifier-Free Evolution

arXiv:2604.07725v1 Announce Type: cross Abstract: We show that verifier-free evolution is bottlenecked by both diversity and efficiency: without external correction, repeated evolution accelerates col

researcharxiv-cs-cl

SSPINNpose: A Self-Supervised PINN for Inertial Pose and Dynamics Estimation

arXiv:2506.11786v2 Announce Type: replace Abstract: Accurate real-time estimation of human movement dynamics, including internal joint moments and muscle forces, is essential for applications in clini

applicationsarxiv-cs-lg

Stabilizing Unsupervised Self-Evolution of MLLMs via Continuous Softened Retracing reSampling

arXiv:2604.03647v2 Announce Type: replace-cross Abstract: In the unsupervised self-evolution of Multimodal Large Language Models, the quality of feedback signals during post-training is pivotal for st

Stacked from One: Multi-Scale Self-Injection for Context Window Extension

arXiv:2603.04759v2 Announce Type: replace Abstract: The limited context window of contemporary large language models (LLMs) remains a primary bottleneck for their broader application across diverse do

State and Trajectory Estimation of Tensegrity Robots via Factor Graphs and Chebyshev Polynomials

arXiv:2604.08185v1 Announce Type: new Abstract: Tensegrity robots offer compliance and adaptability, but their nonlinear, and underconstrained dynamics make state estimation challenging. Reliable cont

applicationsarxiv-cs-ro

Agents

Stay Focused: Problem Drift in Multi-Agent Debate

arXiv:2502.19559v3 Announce Type: replace Abstract: Multi-agent debate - multiple instances of large language models discussing problems in turn-based interaction - has shown promise for solving knowl

agentsarxiv-cs-cl

Tutorials

Steering the Verifiability of Multimodal AI Hallucinations

arXiv:2604.06714v1 Announce Type: new Abstract: AI applications driven by multimodal large language models (MLLMs) are prone to hallucinations and pose considerable risks to human users. Crucially, su

tutorialsarxiv-cs-ai

Stitch4D: Sparse Multi-Location 4D Urban Reconstruction via Spatio-Temporal Interpolation

model-releasesarxiv-cs-cv

arXiv:2604.07923v1 Announce Type: new Abstract: Dynamic urban environments are often captured by cameras placed at spatially separated locations with little or no view overlap. However, most existing

Stochastic Auto-conditioned Fast Gradient Methods with Optimal Rates

model-releasesarxiv-cs-lg

arXiv:2604.06525v1 Announce Type: cross Abstract: Achieving optimal rates for stochastic composite convex optimization without prior knowledge of problem parameters remains a central challenge. In the

Stochastic Gradient Descent in the Saddle-to-Saddle Regime of Deep Linear Networks

arXiv:2604.06366v1 Announce Type: new Abstract: Deep linear networks (DLNs) are used as an analytically tractable model of the training dynamics of deep neural networks. While gradient descent in DLNs

Stop Listening to Me! How Multi-turn Conversations Can Degrade LLM Diagnostic Reasoning

arXiv:2603.11394v2 Announce Type: replace Abstract: Patients and clinicians are increasingly using chatbots powered by large language models (LLMs) for healthcare inquiries. While state-of-the-art LLM

applicationsarxiv-cs-cl

STQuant: Spatio-Temporal Adaptive Framework for Optimizer Quantization in Large Multimodal Model Training

arXiv:2604.06836v2 Announce Type: new Abstract: Quantization is an effective way to reduce the memory cost of large-scale model training. However, most existing methods adopt fixed-precision policies,

Strategic Persuasion with Trait-Conditioned Multi-Agent Systems for Iterative Legal Argumentation

arXiv:2604.07028v1 Announce Type: cross Abstract: Strategic interaction in adversarial domains such as law, diplomacy, and negotiation is mediated by language, yet most game-theoretic models abstract