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SPDEBench: An Extensive Benchmark for Learning Stochastic PDEs

arXiv:2505.18511v2 Announce Type: replace Abstract: Stochastic Partial Differential Equations (SPDEs) driven by random noise play a central role in modeling physical processes with rough spatio-tempor

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speaks for itself Musk's lawyer: 'Are you completely trustworthy?' Altman: 'I believe so.' Musk's lawyer: 'But, you know, you don't know whether you're completely trustworthy.' Altman: 'I'll just amen

safetygary-marcus--x

12 May 2026

SPECTRA-Net: Scalable Pipeline for Explainable Cross-domain Tensor Representations for AI-generated Images Detection

arXiv:2605.08226v1 Announce Type: new Abstract: The rapid proliferation of AI-generated images (AIGI) presents a significant challenge to digital information integrity. While human observers and exist

applicationsarxiv-cs-cv

Spectral Characterization and Mitigation of Sequential Knowledge Editing Collapse

arXiv:2601.11042v2 Announce Type: replace-cross Abstract: Sequential knowledge editing in large language models often causes catastrophic collapse of the model's general abilities, especially for para

Spectral Condition for muP under Width-Depth Scaling

arXiv:2603.00541v2 Announce Type: replace Abstract: Generative foundation models are increasingly scaled in both width and depth, posing significant challenges for stable feature learning and reliable

Spectral Transformer Neural Processes

arXiv:2605.09498v1 Announce Type: cross Abstract: Time series, spatial data, and images are natural applications of Neural Processes. However, when such data exhibit strong periodicity and quasi-perio

safetyarxiv-cs-ai

SpectraLLM: Uncovering the Ability of LLMs for Molecular Structure Elucidation from Multi-Spectral Data

arXiv:2508.08441v3 Announce Type: replace-cross Abstract: Automated molecular structure elucidation remains challenging, as existing approaches often depend on pre-compiled databases or restrict thems

Spectrally-Guided Diffusion Noise Schedules

arXiv:2603.19222v2 Announce Type: replace Abstract: Denoising diffusion models are widely used for high-quality image and video generation. Their performance depends on noise schedules, which define t

researcharxiv-cs-cv

SPECTRE: Hybrid Ordinary-Parallel Speculative Serving for Resource-Efficient LLM Inference

arXiv:2605.08151v1 Announce Type: cross Abstract: LLM serving platforms are increasingly deployed as multi-model cloud systems, where user demand is often long-tailed: a few popular large models recei

applicationsarxiv-cs-ai

Speech-based Psychological Crisis Assessment using LLMs

arXiv:2605.10027v1 Announce Type: cross Abstract: Psychological support hotlines provide critical support for individuals experiencing mental health emergencies, yet current assessments largely rely o

Spherical Boltzmann machines: a solvable theory of learning and generation in energy-based models

arXiv:2605.09031v1 Announce Type: new Abstract: Energy-based models (EBMs) are flexible generative architectures inspired by statistical physics, but their learning and generative properties remain po

Spherical Flows for Sampling Categorical Data

arXiv:2605.05629v2 Announce Type: replace-cross Abstract: We study the problem of learning generative models for discrete sequences in a continuous embedding space. Whereas prior approaches typically

researcharxiv-cs-cl

Split CNN Inference on Networked Microcontrollers

arXiv:2605.09357v1 Announce Type: cross Abstract: Running deep neural networks on microcontroller units (MCUs) is severely constrained by limited memory resources. While TinyML techniques reduce model

SSA: Improving Performance With a Better Scoring Function

arXiv:2508.14685v4 Announce Type: replace Abstract: While transformer models exhibit strong in-context learning (ICL) abilities, they often fail to generalize under simple distribution shifts. We anal

researcharxiv-cs-cl

Stability of the Monge Map in Semi-Dual Optimal Transport

arXiv:2605.05569v2 Announce Type: replace-cross Abstract: This paper shows that the semi-dual formulation of the optimal transport problem has a degenerate saddle-point structure, and that its numeric

Stable Long-Horizon PDE Forecasting via Latent Structured Spectral Propagators

arXiv:2605.10154v1 Announce Type: new Abstract: Long-horizon forecasting of time-dependent partial differential equations (PDEs) is critical for characterizing the sustained evolution of physical syst

Industry

Starlink is now onboard @GulfAir Experience seamless streaming, gaming, and scrolling from gate to gate 🛰️✈️

Starlink is now onboard @GulfAir Experience seamless streaming, gaming, and scrolling from gate to gate 🛰️✈️ We just made history. ✈️🌐 Gulf Air’s first @Starlink flight just took off. Full internet. C

industryelon-musk--x

Industry

Starlink Mobile V2 coming next year will be a game changer for global connectivity! Thank you @FCC

Starlink Mobile V2 coming next year will be a game changer for global connectivity! Thank you @FCC Thanks to President Trump, America is leading the world again. 🇺🇸 Today, the @FCC approved two major

industryelon-musk--x

Statistical Inference and Quality Measures of KV Cache Quantisations Inspired by TurboQuant

arXiv:2605.08114v1 Announce Type: new Abstract: We analyse three KV cache quantization schemes under a fair bit budget: extbf{KV} (scalar MSE baseline), extbf{KQV} (WHT + MSE on K; WHT + MSE + QJL on

Statistical Model Checking of the Keynes+Schumpeter Model: A Transient Sensitivity Analysis of a Macroeconomic ABM

arXiv:2605.10447v1 Announce Type: cross Abstract: Agent-based models (ABMs) are increasingly used in macroeconomics, but their analysis still often relies on ad hoc Monte Carlo campaigns with heteroge

Statistical Scouting Finds Debate-Safe but Not Debate-Useful Cases: A Matched-Ceiling Study of Open-Weight LLM Reasoning Protocols

model-releasesarxiv-cs-cl

arXiv:2605.09618v1 Announce Type: new Abstract: When should a language model answer directly, sample and vote, or engage in multi-agent debate? Recent work shows voting often explains much of the gain

Stealthy Patch-Wise Backdoor Attack in 3D Point Cloud via Curvature Awareness

arXiv:2503.09336v4 Announce Type: replace Abstract: Backdoor attacks pose a severe threat to deep neural networks (DNNs) by implanting hidden backdoors that can be activated with predefined triggers t

researcharxiv-cs-cv

Steerable but Not Decodable: Function Vectors Operate Beyond the Logit Lens

arXiv:2604.02608v2 Announce Type: replace Abstract: Activation steering presupposes that task-relevant behaviors correspond to linear directions in activation space -- directions that should both stee

Stellar Age Compression Reshapes Interpretations of the Milky Way Thick-Disk Formation History

arXiv:2605.10220v1 Announce Type: cross Abstract: The formation timescale of the Milky Way thick disk is one of the central debates in Galactic archaeology. The age-metallicity relation (AMR), formati

Step 3.5 Flash from @StepFun_ai is now free again in Nous Portal for the next 15 days!

Nous Research announced that Step 3.5 Flash, an AI model from StepFun, is temporarily available for free on the Nous Portal for a 15-day period. This offer provides users access to the model without c

researchnous-research--x

Step Rejection Fine-Tuning: A Practical Distillation Recipe

arXiv:2605.10674v1 Announce Type: cross Abstract: Rejection Fine-Tuning (RFT) is a standard method for training LLM agents, where unsuccessful trajectories are discarded from the training set. In the

StereoPolicy: Improving Robotic Manipulation Policies via Stereo Perception

arXiv:2605.09989v1 Announce Type: cross Abstract: Recent advances in robot imitation learning have yielded powerful visuomotor policies capable of manipulating a wide variety of objects directly from

safetyarxiv-cs-cv

Local Ai

StereoTales: A Multilingual Framework for Open-Ended Stereotype Discovery in LLMs

arXiv:2605.10442v1 Announce Type: cross Abstract: Multilingual studies of social bias in open-ended LLM generation remain limited: most existing benchmarks are English-centric, template-based, or rest

local-aiarxiv-cs-ai

Strategic commitments shape collective cybersecurity under AI inequality

arXiv:2605.09415v1 Announce Type: new Abstract: The growing integration of AI into cybersecurity is reshaping the balance between attackers and defenders. When access to advanced AI-enabled defence to

Strategic Exploitation in LLM Agent Markets: A Simulation Framework for E-Commerce Trust

arXiv:2605.10059v1 Announce Type: new Abstract: Agent-based modeling (ABM) has long been used in economics to study human behavior, and large language model (LLM) agents now enable new forms of social

Streaming Sliced Optimal Transport

arXiv:2505.06835v4 Announce Type: replace Abstract: Sliced optimal transport (SOT), or sliced Wasserstein (SW) distance, is widely recognized for its statistical and computational scalability. In this

STRIVE: Structured Spatiotemporal Exploration for Reinforcement Learning in Video Question Answering

arXiv:2604.01824v2 Announce Type: replace Abstract: We introduce STRIVE (SpatioTemporal Reinforcement with Importance-aware Variant Exploration), a structured reinforcement learning framework for vide

safetyarxiv-cs-cv

Structural Alignment Improves Graph Test-Time Adaptation

arXiv:2502.18334v5 Announce Type: replace Abstract: Graph-based learning excels at capturing interaction patterns in diverse domains like recommendation, fraud detection, and particle physics. However

Structure-Centric Graph Foundation Model via Geometric Bases

arXiv:2605.08689v1 Announce Type: cross Abstract: Graph foundation models (GFMs) seek transferable representations across graph domains but are limited by structural heterogeneity and incompatible nod

Structure-Preserving Reconstruction of Convex Lipschitz Functionals on Hilbert Spaces from Finite Samples

arXiv:2605.08559v1 Announce Type: cross Abstract: Convex functionals are ubiquitous in applied analysis, appearing as value functions, risk measures, super-hedging prices, and loss functionals in mach

Structured Recurrent Mixers for Massively Parallelized Sequence Generation

arXiv:2605.08696v1 Announce Type: new Abstract: Over the last two decades, language modeling has experienced a shift from predominantly recurrent architectures that process tokens sequentially during

researcharxiv-cs-cl

Sub-Footprint Effect Correction in FW-LiDAR Point Clouds via Intra-Footprint Target Unmixing

arXiv:2605.09845v1 Announce Type: new Abstract: Sub-footprint target mixing within a laser footprint significantly increases LiDAR intensity uncertainty, especially in complex environments where heter

applicationsarxiv-cs-lg

Sub-JEPA: Subspace Gaussian Regularization for Stable End-to-End World Models

arXiv:2605.09241v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architectures (JEPAs) provide a simpleframework for learning world models by predicting future latent representations.Howev

safetyarxiv-cs-ai

Sufficient conditions for a Heuristic Rating Estimation Method application

arXiv:2605.08991v1 Announce Type: new Abstract: A series of papers has introduced the Heuristic Rating Estimation method, which evaluates a set of alternatives based on pairwise comparisons and the we

Summary: An International Agreement to Prevent the Premature Creation of Artificial Superintelligence

If anyone, anywhere builds a superhuman artificial intelligence using present methods, the most likely outcome is catastrophe. There have accordingly been widespread calls for an international agreeme

safetymiri

Sundial: A Family of Highly Capable Time Series Foundation Models

arXiv:2502.00816v4 Announce Type: replace Abstract: We introduce Sundial, a family of native, flexible, and scalable time series foundation models. To predict the next-patch's distribution, we propose

applicationsarxiv-cs-lg

Supercharging Bayesian Inference with Reliable AI-Informed Priors

arXiv:2605.09834v1 Announce Type: cross Abstract: Modern predictive systems encode beliefs that can act as useful prior information for statistical inference in data-limited settings. Using them for p

Supersampling Stable Diffusion and More: An Approach for Interpolating Neural Networks Using Common Interpolation Methods

arXiv:2605.08698v1 Announce Type: new Abstract: Stable Diffusion (SD) has evolved DDPM (Denoising Diffusion Probabilistic Model) based image generation significantly by denoising in latent space inste

researcharxiv-cs-cv

Supervised Dimensionality Reduction Revisited: Why LDA on Frozen CNN Features Deserves a Second Look

arXiv:2604.03928v2 Announce Type: replace-cross Abstract: Frozen pretrained image representations are widely used for transfer learning: a backbone is kept fixed, feature vectors are extracted, and a

Supervised Guidance Training for Infinite-Dimensional Diffusion Models

arXiv:2601.20756v2 Announce Type: replace Abstract: Score-based diffusion models have recently been extended to infinite-dimensional function spaces, with uses such as inverse problems arising from pa

Supervised Mixture-of-Experts for Surgical Grasping and Retraction

arXiv:2601.21971v2 Announce Type: replace-cross Abstract: Imitation learning has achieved remarkable success in robotic manipulation, yet its application to surgical robotics remains challenging due t

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Industry

Surreal to see Reachy Mini on the cover of the last @LinusTech video!

Clem Delangue, CEO of Hugging Face, shared excitement about seeing Reachy Mini, a small humanoid robot, featured on the cover of Linus Tech Tips' latest video. The post suggests Reachy Mini received n

industryclem-delangue--x

Survey-aware Machine Learning: A Guideline for Valid Population Health Inference based on Scoping Review

arXiv:2605.08963v1 Announce Type: cross Abstract: Machine Learning (ML) models trained on complex health surveys such as the National Health and Nutrition Examination Survey (NHANES) often ignore prim