All entries

arXiv:2605.02413v1 Announce Type: cross Abstract: In this paper, we propose a spatial-temporal learning-based distributed routing framework for dynamic Low Earth Orbit (LEO) satellite networks, where

local-aiarxiv-cs-lg

Spatiotemporal Hidden-State Dynamics as a Signature of Internal Reasoning in Large Language Models

DGX agent

arXiv:2605.01853v1 Announce Type: new Abstract: Large reasoning models (LRMs) generate extended solutions, yet it remains unclear whether these traces reflect substantive internal computation or merel

researcharxiv-cs-cl

5 May 2026

SpecEdit: Training-Free Acceleration for Diffusion based Image Editing via Semantic Locking

arXiv:2605.02152v1 Announce Type: new Abstract: Diffusion-based image editing offers strong semantic controllability, but remains computationally expensive due to iterative high-resolution denoising o

SpecKV: Adaptive Speculative Decoding with Compression-Aware Gamma Selection

arXiv:2605.02888v1 Announce Type: cross Abstract: Speculative decoding accelerates large language model (LLM) inference by using a small draft model to propose candidate tokens that a larger target mo

researcharxiv-cs-cl

Tutorials

SpecTM: Spectral Targeted Masking for Trustworthy Foundation Models

arXiv:2603.22097v2 Announce Type: replace-cross Abstract: Foundation models are now increasingly being developed for Earth observation (EO), yet they often rely on stochastic masking that do not expli

tutorialsarxiv-cs-lg

SpectraDINO: Bridging the Spectral Gap in Vision Foundation Models via Lightweight Adapters

arXiv:2605.02258v1 Announce Type: new Abstract: Vision Foundation Models (VFMs) pretrained on large-scale RGB data have demonstrated remarkable representation quality, yet their applicability to multi

safetyarxiv-cs-cv

Spectral Graph Sparsification Preserves Representation Geometry in Graph Neural Networks

arXiv:2605.01136v1 Announce Type: new Abstract: Spectral graph sparsification is a classical tool for reducing graph complexity while preserving Laplacian quadratic forms. In graph neural networks (GN

Spectral Model eXplainer: a chemically-grounded explainability framework for spectral-based machine learning models

arXiv:2605.02684v1 Announce Type: new Abstract: Spectral-based machine learning models have been increasingly deployed in chemometrics and spectroscopy, where predictive accuracy is as important as ex

SplAttN: Bridging 2D and 3D with Gaussian Soft Splatting and Attention for Point Cloud Completion

arXiv:2605.01466v1 Announce Type: new Abstract: Although multi-modal learning has advanced point cloud completion, the theoretical mechanisms remain unclear. Recent works attribute success to the conn

Split-on-Share: Mixture of Sparse Experts for Task-Agnostic Continual Learning

arXiv:2601.17616v2 Announce Type: replace Abstract: Continual learning in Large Language Models (LLMs) is hindered by the plasticity-stability dilemma, where acquiring new capabilities often leads to

Hardware

SplitZip: Ultra Fast Lossless KV Compression for Disaggregated LLM Serving

arXiv:2605.01708v1 Announce Type: cross Abstract: Contemporary systems serving large language models (LLMs) have adopted prefill-decode disaggregation to better load-balance between the compute-bound

hardwarearxiv-cs-lg

Spoken Language Identification with Pre-trained Models and Margin Loss

arXiv:2605.01905v1 Announce Type: cross Abstract: For the speaker-controlled spoken language identification task proposed in the TidyLang Challenge 2026, this paper proposes a language identification

SRA: Span Representation Alignment for Large Language Model Distillation

arXiv:2605.01205v1 Announce Type: new Abstract: Cross-Tokenizer Knowledge Distillation (CTKD) enables knowledge transfer between a large language model and a smaller student, even when they employ dif

safetyarxiv-cs-cl

SRGAN-CKAN: Expressive Super-Resolution with Nonlinear Functional Operators under Minimal Resources

arXiv:2605.01459v1 Announce Type: new Abstract: Single-Image Super-Resolution (SISR) aims to reconstruct a High-Resolution (HR) image from a Low-Resolution (LR) observation, a fundamentally ill-posed

researcharxiv-cs-cv

SRTJ: Self-Evolving Rule-Driven Training-Free LLM Jailbreaking

arXiv:2605.00974v1 Announce Type: cross Abstract: LLMs are increasingly equipped with safety alignment mechanisms, yet recent studies demonstrate that they remain vulnerable to jailbreaking attacks th

Stability and Generalization for Decentralized Markov SGD

arXiv:2605.01701v1 Announce Type: new Abstract: Stochastic gradient methods are central to large-scale learning, yet their generalization theory typically relies on independent sampling assumptions. I

Stability of Control Lyapunov Function Guided Reinforcement Learning

arXiv:2605.01978v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become the de facto method for achieving locomotion on humanoid robots in practice, yet stability analysis of the corr

researcharxiv-cs-ro

Stabilizing Private LASSO under Heterogeneous Covariates via Anisotropic Objective Perturbation

arXiv:2605.01492v1 Announce Type: cross Abstract: We study high-dimensional LASSO under differential privacy via objective perturbation with heterogeneous covariate scales. In practical scenarios, cov

Stable Blanket with Hidden Variables and Cycles

arXiv:2605.01856v1 Announce Type: cross Abstract: Stabilized regression aims to identify a set of predictors whose conditional relationship with a response variable remains invariant across different

Tutorials

Stable GFlowNets with Probabilistic Guarantees

arXiv:2605.01729v1 Announce Type: new Abstract: Generative Flow Networks (GFlowNets) learn to sample states proportional to an unnormalized reward. Despite their theoretical promise, practical trainin

tutorialsarxiv-cs-lg

Stable Localized Conformal Prediction via Transduction

arXiv:2605.01452v1 Announce Type: cross Abstract: Existing evaluations of conformal prediction, such as prediction efficiency and test-conditional coverage, are defined in expectation over the calibra

StableMind: Source-Free Cross-Subject fMRI Decoding with Regularized Adaptation

arXiv:2605.02586v1 Announce Type: new Abstract: Existing cross-subject fMRI decoding methods typically train a model on multiple scanned subjects and then adapt it to a new subject using substantial p

safetyarxiv-cs-cv

STABLEVAL: Disagreement-Aware and Stable Evaluation of AI Systems

arXiv:2605.02122v1 Announce Type: new Abstract: Human evaluation remains the primary standard for assessing modern AI systems, yet annotator disagreement, bias, and variability make system rankings fr

safetyarxiv-cs-lg

STAGE: A Full-Screenplay Benchmark for Reasoning over Evolving Storie

arXiv:2601.08510v3 Announce Type: replace Abstract: Movie screenplays are rich long-form narratives that interleave complex character relationships, temporally ordered events, and dialogue-driven inte

Standing on the Shoulders of Giants: Stabilized Knowledge Distillation for Cross--Language Code Clone Detection

arXiv:2605.02860v1 Announce Type: cross Abstract: Cross-language code clone detection (X-CCD) is challenging because semantically equivalent programs written in different languages often share little

STAR: Decode-Phase Rescheduling for LLM Inference

arXiv:2510.13668v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) inference has emerged as a fundamental paradigm, however, variations in output length cause severe workload imbalan

Statistical Consistency and Generalization of Contrastive Representation Learning

arXiv:2605.02116v1 Announce Type: new Abstract: Contrastive representation learning (CRL) underpins many modern foundation models. Despite recent theoretical progress, existing analyses suffer from se

Statistically-Lossless Quantization of Large Language Models

arXiv:2605.02404v1 Announce Type: new Abstract: Model quantization has become essential for efficient large language model deployment, yet existing approaches involve clear trade-offs: methods such as

SteeringDiffusion: A Bottlenecked Activation Control Interface for Diffusion Models

arXiv:2605.01653v1 Announce Type: new Abstract: We introduce SteeringDiffusion, a bottlenecked activation-level control interface for diffusion models that exposes a smooth, monotonic, and runtime-adj

STEP: Warm-Started Visuomotor Policies with Spatiotemporal Consistency Prediction

model-releasesarxiv-cs-ro

arXiv:2602.08245v2 Announce Type: replace Abstract: Diffusion policies have recently emerged as a powerful paradigm for visuomotor control in robotic manipulation due to their ability to model the dis

StereoMamba: Real-time and Robust Intraoperative Stereo Disparity Estimation via Long-range Spatial Dependencies

arXiv:2504.17401v2 Announce Type: replace Abstract: Stereo disparity estimation is crucial for obtaining depth information in robot-assisted minimally invasive surgery (RAMIS). While current deep lear

Applications

Stochastic Modeling of Human-Machine Authentication Channels under Partial Information Leakage

arXiv:2605.02102v1 Announce Type: cross Abstract: Reliable and secure human-machine communication is fundamental to IoT and cyber-physical ecosystems, where smartphones and wearables commonly serve as

applicationsarxiv-cs-lg

Hardware

Stochastic Sparse Attention for Memory-Bound Inference

arXiv:2605.01910v1 Announce Type: new Abstract: Autoregressive decoding becomes bandwidth-limited at long contexts, as generating each token requires reading all n_k key and value vectors from KV cach

hardwarearxiv-cs-lg

StreamIndex: Memory-Bounded Compressed Sparse Attention via Streaming Top-k

arXiv:2605.02568v1 Announce Type: new Abstract: DeepSeek-V3.2 and V4 introduce Compressed Sparse Attention (CSA): a lightning indexer (a learned scoring projection over compressed keys) scores them, t

Industry

Streamlining generative AI development with MLflow v3.10 on Amazon SageMaker AI

Today, we’re excited to announce that Amazon SageMaker AI MLflow Apps now support MLflow version 3.10, bringing enhanced capabilities for generative AI development and streamlined experiment tracking

industryaws-ml-blog

StressEval: Failure-Driven Dynamic Benchmarking for Knowledge-Intensive Reasoning in Large Language Models

arXiv:2605.01939v1 Announce Type: new Abstract: Static benchmarks for LLMs are increasingly compromised by contamination and overfitting especially on knowledge intensive reasoning tasks While recent

Applications

Structural Dilemmas and Developmental Pathways of Legal Argument Mining in the Era of Artificial Intelligence

arXiv:2605.02308v1 Announce Type: new Abstract: Against the backdrop of rapid advances in artificial intelligence, legal argument mining has emerged as an important research area linking legal texts w

applicationsarxiv-cs-cl

Structured Analytic Coherent Point Drift for Non-Rigid Point Set Registration

arXiv:2605.00934v1 Announce Type: new Abstract: We introduce Analytic-CPD, a structured analytic variant of coherent point drift for non-rigid point set registration. The method retains the CPD poster

StyleShield: Exposing the Fragility of AIGC Detectors through Continuous Controllable Style Transfer

arXiv:2605.00924v1 Announce Type: new Abstract: AI-generated content (AIGC) detectors are increasingly deployed in high-stakes settings such as academic integrity screening, yet their reliability rest

Stylistic Attribute Control in Latent Diffusion Models

arXiv:2605.02583v1 Announce Type: new Abstract: Text-to-image diffusion models have revolutionized image synthesis and editing, but precise control over stylistic attributes remains a challenge, often

researcharxiv-cs-cv

Submodular Benchmark Selection

arXiv:2605.02209v1 Announce Type: cross Abstract: Evaluating large language models across many benchmarks is expensive, yet many benchmarks are highly correlated. We formalize the selection of a small

Subquadratic launches with $29M to bring 12M-token context windows to AI

model-releasessiliconangle

Subquadratic, a company developing a novel generative artificial intelligence model, launched today with 29 million in seed funding. The new large language model, dubbed SubQ, uses what the company ca

Agents

SUDP: Secret-Use Delegation Protocol for Agentic Systems

arXiv:2604.24920v2 Announce Type: replace-cross Abstract: Agentic systems increasingly act with user secrets for APIs, messaging platforms, and cloud services. Today's bearer-secret interfaces impleme

agentsarxiv-cs-ai

Industry

Super Micro reports Q3 revenue up 123% YoY to 10.24B, vs. 12.33B est., forecasts Q4 revenue and adjusted profit above estimates; SMCI jumps 17%+ after hours (Juby Babu/Reuters)

Juby Babu / Reuters: Super Micro reports Q3 revenue up 123% YoY to 10.24B, vs. 12.33B est., forecasts Q4 revenue and adjusted profit above estimates; SMCI jumps 17%+ after hours — Super Micro Computer

industrytechmeme

Local Ai

Super-resolution of airborne laser scanning point clouds for forest inventory

arXiv:2605.02201v1 Announce Type: new Abstract: Airborne Laser Scanning (ALS) can collect point clouds across large areas, enabling large-scale forest inventory. However, ALS point clouds are sparse a

local-aiarxiv-cs-cv

Industry

Supermicro shares rally on guidance after Q3 revenue falls short of estimates

Super Micro Computer Inc.’s shares surged more than 18% in after-hours trading today after the server maker reported a mixed fiscal 2026 third quarter, missing revenue estimates but topping earnings e

industrysiliconangle

Tutorials

Sure looks like Bun is at least exploring a port from Zig to Rust given this docs/PORTING.md guide for coding agents https://github.com/oven…

tutorialssimon-willison--x

Sure looks like Bun is at least exploring a port from Zig to Rust given this docs/PORTING.md guide for coding agents https://github.com/oven-sh/bun/blob/46d3bc29f270fa881dd5730ef1549e88407701a5/docs/P

SurgCheck: Do Vision-Language Models Really Look at Images in Surgical VQA?

arXiv:2605.01911v1 Announce Type: new Abstract: Purpose: Vision-language models (VLMs) have shown promising performance in surgical visual question answering (VQA). However, existing surgical VQA data