All entries

Smooth Neural Point Processes via B-Splines

arXiv:2607.21098v1 Announce Type: new Abstract: Temporal point processes (TPPs) provide a general and flexible framework for modeling sequences of events in continuous time. Neural networks have been

applicationsarxiv-cs-lg

SOAP, Muon, and Beyond: Pushing LLM Pretraining Scales

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arXiv:2607.20548v1 Announce Type: cross Abstract: Higher-order optimizers such as Muon and SOAP offer faster convergence than AdamW, but their computational cost and numerical stability challenges hav

model-releasesarxiv-cs-ai

24 Jul 2026

SoccerSynth Field: enhancing field detection with synthetic data from virtual soccer simulator

arXiv:2503.13969v2 Announce Type: replace Abstract: Field detection in team sports is an essential task in sports video analysis. However, collecting large-scale and diverse real-world datasets for tr

applicationsarxiv-cs-cv

Socially Consistent Multi-Robot Navigation Using Decoupled Planning and Trajectory Coordination

arXiv:2607.20772v1 Announce Type: new Abstract: The successful integration of mobile robots in human-centric environments requires navigation that is not only safe and efficient, but also predictable

researcharxiv-cs-ro

SonicSampler: Unified Tile-Aware Kernels for LLM Sampling and Speculative Verification

arXiv:2607.20475v1 Announce Type: new Abstract: Sampling in LLM inference comprises a combinatorial set of logit processing, token selection, and verification operations for speculative decoding. Howe

Source-Prior-Driven Selective Adaptation for Efficient Diffusion Model Finetuning

arXiv:2607.20913v1 Announce Type: new Abstract: Fine-tuning large diffusion models for new domains or styles involves a trade-off: improving target-specific generation often degrades the pretrained mo

Industry

Sources: OpenAI told Hugging Face only this week its models caused the July 11 hack; the models appear to have been active online for days before being stopped (Wall Street Journal)

Wall Street Journal: Sources: OpenAI told Hugging Face only this week its models caused the July 11 hack; the models appear to have been active online for days before being stopped — They were like hi

industrytechmeme

Agents

Sources: OpenAI's models breached Hugging Face from July 11 to 13 and OpenAI realized their models were behind the hack several days later (Reuters)

Reuters: Sources: OpenAI's models breached Hugging Face from July 11 to 13 and OpenAI realized their models were behind the hack several days later — The OpenAI agent that broke into tech firm Hugging

agentstechmeme

Sparse Concept Channels in Frozen 3D CT Vision Encoders

arXiv:2607.20993v1 Announce Type: cross Abstract: Large vision-language models are becoming increasingly dominant in 3D medical image interpretation, but we rarely know which internal units encode cli

researcharxiv-cs-ai

Spatially Grounded Concept Bottleneck Models for Trustworthy Breast Ultrasound Diagnosis

arXiv:2607.20691v1 Announce Type: cross Abstract: Concept Bottleneck Models provide interpretable-by-design predictions by mediating diagnosis through human-understandable concepts, but in medical ima

safetyarxiv-cs-ai

SPDCN: Strip-based Deformable Convolutional Network for Steel Surface Defect Segmentation

arXiv:2607.21456v1 Announce Type: new Abstract: Steel surface defect segmentation is critical for industrial quality inspection, yet existing methods struggle with elongated, anisotropic defects such

researcharxiv-cs-cv

SPECTRA: State-Space Exogenous Context and Temporal-Frequency Resolution Architecture for Probabilistic Energy Forecasting

arXiv:2607.20587v1 Announce Type: cross Abstract: Modern power systems increasingly require probabilistic forecasts amid interacting uncertainties from renewable intermittency, flexible demand, market

safetyarxiv-cs-lg

Spectral Concentration and Recovery in Sparse High-Dimensional Random Geometric Graphs

arXiv:2607.14304v2 Announce Type: replace-cross Abstract: We study sparse threshold random geometric graphs generated by high-dimensional spherical or Gaussian latent vectors. Although each edge has m

Spectral functions in Minkowski quantum electrodynamics from neural reconstruction

model-releasesarxiv-cs-lg

arXiv:2510.24728v2 Announce Type: replace-cross Abstract: We study neural reconstructions of quenched rainbow quantum electrodynamics (QED) Dyson--Schwinger benchmarks in Minkowski-related kinematics.

Spectral-Spatial Synergistic Guided Network for Hyperspectral Salient Object Detection

model-releasesarxiv-cs-cv

arXiv:2607.21032v1 Announce Type: new Abstract: Hyperspectral salient object detection aims to identify visually salient regions from hyperspectral images. Existing methods often fail because they fun

Local Ai

Spectral Transformation for Layer-wise Global Rank Discovery in Federated LoRA for Vision Transformers

arXiv:2607.21074v1 Announce Type: new Abstract: Fine-tuning Vision Transformers (ViTs) with low-rank adapters (LoRA) promises better communication efficiency under federated setup, yet existing aggreg

local-aiarxiv-cs-lg

Local Ai

Spent two weeks on a kernel that benchmarked 29x faster. End to end it's maybe 6-10%, and it's not even wired in yet.

I've been building a C99 inference engine from scratch (no Python, no BLAS, just gcc and make) that runs BitNet's ternary models on CPU. A few weeks ago I got obsessed with the matmul kernel - wrote a

local-air-localllama

Hardware

SPORD: A Simulation-Propose-then-OR-Dispose Approach for Supply Chain Planning

arXiv:2607.21354v1 Announce Type: new Abstract: For years, supply chain planning at e-commerce firms has operated as a collection of isolated projects. Each planning task from static network planning

hardwarearxiv-cs-ai

Tutorials

SR-TTT Does Not Learn Retrieval: A Correction and Mechanistic Post-Mortem of Surprisal-Aware Residual Test-Time Training

arXiv:2603.06642v2 Announce Type: replace-cross Abstract: Test-Time Training (TTT) language models replace the KV-cache with fast weights updated during inference, achieving O(1) memory but suffering

tutorialsarxiv-cs-ai

StabilityBench: Benchmarking Instability in LLMs

arXiv:2607.20558v1 Announce Type: cross Abstract: AI Assistants are increasingly deployed in high-stakes settings, such as healthcare or government services. Yet their real-world behavior remains poor

Statistical Inference for Generative Model Comparison

model-releasesarxiv-cs-lg

arXiv:2501.18897v4 Announce Type: replace-cross Abstract: Generative models have achieved remarkable success across a range of applications, yet their evaluation still lacks principled uncertainty qua

Tutorials

Statistical physics of deep learning: Optimal learning of a multi-layer perceptron near interpolation

arXiv:2510.24616v4 Announce Type: replace-cross Abstract: For four decades statistical physics has been providing a framework to analyse neural networks. A long-standing question remained on its capac

tutorialsarxiv-cs-lg

Statistics of week: “More Americans pay for sports betting apps (5%) than pay for AI… 37% of consumers say none of AI's uses are helpful. … …

Statistics of week: “More Americans pay for sports betting apps (5%) than pay for AI… 37% of consumers say none of AI's uses are helpful. … 2.2% penetration nearly four years after ChatGPT launched. N

safetygary-marcus--x

Stay hungry, stay foolish. Absolute legend

Stay hungry, stay foolish. Absolute legend For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by ever

safetyjim-fan--x

Tutorials

STeMP: Spatio-Temporal Modelling Protocol

arXiv:2607.20592v1 Announce Type: new Abstract: Spatio-temporal machine-learning modelling is an important tool in environmental research. However, machine-learning models are highly sensitive to both

tutorialsarxiv-cs-lg

Stochastic Sampling is Epistemically Shallow: The Dimensionality Gap Between Temperature Variation and Model Diversity in LLMs

arXiv:2607.20464v1 Announce Type: new Abstract: When a language model gives different answers on repeated runs, does that variation reveal what it does not know? Self-consistency turns the variation i

researcharxiv-cs-ai

Stokes-Informed Diffusion for Robust Linear Polarization Estimation

arXiv:2607.21239v1 Announce Type: new Abstract: Polarization cues benefit applications such as material detection and de-reflection, yet acquiring them typically requires dedicated hardware. This moti

safetyarxiv-cs-cv

Agents

Streaming Multi-Agent Autoregressive Diffusion Model with World State Registers

arXiv:2607.21594v1 Announce Type: new Abstract: Multi-agent interactive world models should not only generate consistent observations, but also maintain world states that persist across agents and evo

agentsarxiv-cs-cv

StrideDiffusion: Accelerating Diffusion Models for Time-series Generation

arXiv:2607.20545v1 Announce Type: new Abstract: Diffusion models have become competitive generators for time series, but their practical use is limited by the large number of sequential denoising step

researcharxiv-cs-ai

Structure-Preserving Physics-Informed Neural Network for the Korteweg--de Vries (KdV) Equation

arXiv:2511.00418v2 Announce Type: replace Abstract: Physics-Informed Neural Networks (PINNs) offer a flexible framework for solving nonlinear partial differential equations (PDEs), yet conventional im

Student-Centered Distillation Narrows the Agentic Gap Between Small and Large LLMs

arXiv:2509.14257v3 Announce Type: replace-cross Abstract: Large Language Model agents achieve strong performance on multi-step reasoning and tool-use tasks, but their impressive capabilities typically

SubSplat: High-Resolution Pixel-aligned 3DGS via Sub-pixel Gaussian Reparameterization

arXiv:2607.20813v1 Announce Type: new Abstract: Pixel-aligned Gaussian splatting enables efficient and generalizable novel-view synthesis. However, high-resolution rendering faces a critical trade-off

researcharxiv-cs-cv

SuperFlow: Training Flow Matching Models with RL on the Fly

arXiv:2512.17951v3 Announce Type: replace Abstract: Recent progress in flow-based generative models and reinforcement learning (RL) has improved text-image alignment and visual quality. However, curre

safetyarxiv-cs-cv

Surprisal Theory is Tautological (without Rational Grounding)

arXiv:2607.21574v1 Announce Type: new Abstract: Surprisal theory holds that the human processing difficulty of a linguistic unit in context is an affine function of its surprisal under some language m

researcharxiv-cs-cl

swiss-ai/Apertus-v1.5 70B/8B

model-releasesr-localllama

https://huggingface.co/swiss-ai/Apertus-v1.5-70B https://huggingface.co/swiss-ai/Apertus-v1.5-8B Apertus 1.5 is a family of 8B and 70B parameter language models designed to advance the state of multil

Hardware

Synopsys targets physical AI complexity with co-design and agentic chip workflows

The rapid evolution of intelligent software-defined systems is pushing chip design into a new era of physical AI, one where chip design complexity is outpacing traditional engineering methods. Manufac

hardwaresiliconangle

Synthetic data generation framework for quality control automation in gravure printing

arXiv:2607.21577v1 Announce Type: cross Abstract: Quality control in printing, particularly in rotogravure printing, still depends on slow, costly, and subjective manual inspection. Automated surface

applicationsarxiv-cs-ai

Synthetic minority data is redundant or invalid: a data-dependent validity theory and a de-biased test

arXiv:2607.20787v1 Announce Type: cross Abstract: For two decades, the standard remedy for class-imbalanced learning has been to fabricate synthetic minority examples, and the standard evidence of the

safetyarxiv-cs-ai

T-STAR: A Large-Scale Benchmark for Spatio-Temporal Panoptic Scene Graph Generation in Satellite Video

model-releasesarxiv-cs-cv

arXiv:2607.21228v1 Announce Type: new Abstract: Structured understanding of satellite video is essential for advancing dynamic geospatial scene analysis from low-level perception to high-level cogniti

TableVerse: A Large-scale Tabletop Dataset with Real-world Grounded Layouts for Generalizable Manipulation

arXiv:2607.21017v1 Announce Type: new Abstract: The development of generalizable robotic manipulation policies is inherently bounded by the availability of large-scale, high-fidelity scene data. While

applicationsarxiv-cs-ro

TabPFN beyond Tabular Data: Calibration and Accuracy on Multimodal Embeddings

arXiv:2607.11007v2 Announce Type: replace Abstract: Few-shot multimodal classification commonly attaches a lightweight head, such as k-nearest neighbors, logistic regression, or a linear SVM, to a fro

Tackling Heterogeneity in Federated Learning via Variance-Reduced Boltzmann Sampling within Homogeneous Social Coalitions

arXiv:2506.02897v3 Announce Type: replace Abstract: Federated Learning (FL) enables privacy-preserving collaborative model training, but its effectiveness is often limited by client data heterogeneity

Agents

TeaRAG: A Token-Efficient Agentic Retrieval-Augmented Generation Framework

arXiv:2511.05385v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) utilizes external knowledge to augment Large Language Models' (LLMs) reliability. For flexibility, agenti

agentsarxiv-cs-ai

Telco-GAIA: Bilingual Benchmark for Agents in Telecom Domain

arXiv:2607.20510v1 Announce Type: new Abstract: We introduce Telco-GAIA, a bilingual, multi-modal benchmark for evaluating tool-using agents on the data of a real-world telecommunications operator. Te

Tencent WorkBuddy Bench: A Multi-Domain Coding-Agent Benchmark with Contamination-Resistant Task Construction

model-releasesarxiv-cs-cl

arXiv:2607.20911v1 Announce Type: new Abstract: We introduce Tencent WorkBuddy Bench, a multi-domain evaluation suite for coding agents; this report documents its construction methodology, scoring pro

Local Ai

Test-Time Scaling via Error Localization

arXiv:2607.21453v1 Announce Type: new Abstract: Scaling inference-time computation has emerged as a reliable method to improve the performance of large language models on complex reasoning and program

local-aiarxiv-cs-lg

Texture++: Elevating 3D Asset Texture Resolution with a Region-Aware Diffusion Model

arXiv:2607.21504v1 Announce Type: new Abstract: Numerous 3D assets are discarded due to low texture resolution, while current super-resolution models ignore texture maps and focus on natural images. A

researcharxiv-cs-cv

thaulab@EEUCA 2026: Who Said What to Whom? A Targeting-Aware Neural-Symbolic Pipeline for Gaming Toxicity Detection

arXiv:2607.20447v1 Announce Type: new Abstract: This paper describes our system for the EEUCA 2026 Shared Task on toxicity classification in gaming chat. We implement a three-stage pipeline combining

safetyarxiv-cs-cl