All entries

Strong Gravitational Lensing Posterior Sampling in Pixel-Space Using Diffusion Models and Recurrent Inference Machines

arXiv:2607.19459v1 Announce Type: cross Abstract: Modeling galaxy-galaxy strong gravitational lenses to infer the brightness of the source galaxy and the mass distribution of the foreground galaxy is

Safety

Structured Latent Space Modeling over Multi-Scale Temporal Patches for Multivariate Time Series Forecasting

DGX agent

arXiv:2607.19404v1 Announce Type: cross Abstract: Multivariate time series encode structural patterns that unfold across multiple temporal scales, yet most forecasting backbones treat learned represen

safetyarxiv-cs-ai

23 Jul 2026

Applications

STS-NET: Spatio-Temporal Stress Network for Self-Supervised Crop Stress Detection using Satellite Image Time Series

arXiv:2607.18791v1 Announce Type: new Abstract: Early and accurate detection of crop stress is essential to improve agricultural productivity and ensure global food security. However, collecting a lar

applicationsarxiv-cs-cv

Style over Substance: A Shortcut Audit of Emotion-Description Preference Evaluation

arXiv:2607.18508v1 Announce Type: new Abstract: Preference over model-generated emotion descriptions is emerging as a standard evaluation metric for multimodal emotion understanding, exemplified by th

safetyarxiv-cs-cv

Local Ai

Sudo authentication fails when trying to access local models folder on Fedora

When trying to access the models folder on /usr/share/ollama, I'm asked to authenticate as sudo, which weirdly enough, fails. I type my password, which I'm sure is correct since I use it several time

local-air-ollama

SUM: Unified Geometric Surgery on Spatio-Temporal Adaptation Vectors for Federated Class Incremental Learning

model-releasesarxiv-cs-lg

arXiv:2607.19384v1 Announce Type: new Abstract: Real-world intelligent systems often require both distributed collaboration across data-isolated clients and continual adaptation to evolving tasks. Thi

SUPER Module for Detail-Sensitive and Cost-Efficient U-Net Variant Decoders

arXiv:2511.11015v2 Announce Type: replace Abstract: Skip-connected U-Net variants are widely used for dense inverse problems, yet their decoders commonly recover resolution through spatial upscaling,

surprisal is Not a Theory

arXiv:2607.20208v1 Announce Type: new Abstract: Surprisal Theory is often characterized as a computational-level explanation per (Marr, 1982). We argue in this work that, even though a computational l

researcharxiv-cs-cl

Surprise Forcing: What to Remember, When to Skip in Long Video Generation

arXiv:2607.18436v1 Announce Type: new Abstract: Streaming autoregressive diffusion makes minute-scale video synthesis practical, but its bounded context and fixed denoising schedule allocate resources

SwiftGS: Episodic Priors for Immediate Satellite Surface Recovery

arXiv:2603.18634v3 Announce Type: replace-cross Abstract: Rapid, large-scale 3D reconstruction from multi-date satellite imagery is vital for environmental monitoring, urban planning, and disaster res

Tutorials

SWITi: Quantifying and Reducing Tiling Artifacts with Sliding Window Inner Tiling

arXiv:2607.18990v1 Announce Type: new Abstract: SWITi is a test-time method for reducing artifacts in tiled predictions, particularly for neural networks that learn posterior distributions from which

tutorialsarxiv-cs-cv

Agents

Symbol and Footprint Database for Electronic Components by Agentic Recognition and Generation

arXiv:2607.19767v1 Announce Type: new Abstract: A rich and recognizable component library is the cornerstone of printed circuit board (PCB) design and generation. Traditionally, engineers manually cre

agentsarxiv-cs-ai

SynGallery: A Synthetic Gallery of Real Paintings for Instance-Level Artwork Recognition

model-releasesarxiv-cs-cv

arXiv:2607.18907v1 Announce Type: new Abstract: Instance-level artwork recognition requires matching a handheld visitor photograph to a specific work in a large museum collection. This is challenging

Local Ai

SynPre-FL: Synthetic data-driven pretraining integrated Federated Learning training framework

arXiv:2607.19524v1 Announce Type: cross Abstract: Federated learning (FL) offers a promising approach to privacy-preserving clinical risk prediction, but its deployment remains limited by restricted d

local-aiarxiv-cs-ai

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n

arXiv:2607.19535v2 Announce Type: new Abstract: Incorrect disposal can contaminate campus recycling streams, and a bin-mounted camera could provide feedback as an item is discarded. We evaluated wheth

TalentCLEF at CLEF2026: Skill and Job Title Intelligence for Human Capital Management

arXiv:2607.20009v1 Announce Type: new Abstract: This paper presents the second edition of the TalentCLEF Challenge, which will run as an evaluation lab as part of CLEF 2026. The aim of TalentCLEF is t

safetyarxiv-cs-cl

Taming the Security-Energy Paradox: A Green AI Approach to Optimized Android Malware Detection

arXiv:2607.20003v1 Announce Type: cross Abstract: An increase in advanced Android malware requires the use of deep learning models, which can run on Android devices. But there is a trade-off between s

researcharxiv-cs-ai

TAP-RAG: Task-Aware Policy Control for Long-Document Multimodal Question Answering

arXiv:2607.18917v1 Announce Type: new Abstract: Long-document multimodal question answering requires more than retrieving relevant chunks from a large document. Different queries require different evi

safetyarxiv-cs-cv

Task Competence Is Not Instruction Following: Evaluating Instruction-Conflicting Behavior in Small Language Models

model-releasesarxiv-cs-cl

arXiv:2607.19608v1 Announce Type: new Abstract: Instruction tuning is meant to make language models follow user requests, yet it is unclear whether small models comply when an instruction conflicts wi

Team RAS in 11th ABAW Competition: Multimodal Ambivalence Recognition Approach

arXiv:2607.14702v2 Announce Type: replace Abstract: Automatic recognition of ambivalence and hesitancy is challenging because these states may be expressed through inconsistent linguistic, acoustic, f

Tensor Network Machine Learning for Wildfire Susceptibility Mapping: from Grokking Dynamics to Quantum Mixedness of Class Representations

arXiv:2607.19503v1 Announce Type: cross Abstract: A quantum-inspired tensor network framework for wildfire susceptibility classification in the Gargano region is introduced, leveraging AlphaEarth embe

Test Case Prioritization for DNNs via Neural Collapse Instability

arXiv:2607.20046v1 Announce Type: cross Abstract: With the widespread deployment of deep neural networks (DNNs) in safety-critical domains, reducing the cost of model validation under limited testing

safetyarxiv-cs-ai

Test-Time Registers as Global Priors for Tokenized Image Generation

arXiv:2607.16824v2 Announce Type: replace Abstract: Attention-based models often develop attention sinks, where a small number of tokens repeatedly attract attention and accumulate unusually large act

safetyarxiv-cs-cv

Test-Time Training for Modality Order Consistency in Vision-Language Models

arXiv:2607.20351v1 Announce Type: cross Abstract: We find that vision-language models are sensitive to a specific semantically irrelevant change: the order in which the image and question are presente

researcharxiv-cs-cl

Applications

Text-conditioned Segmentation for Tomato Phenotyping via Procedural Synthetic Data

arXiv:2607.18576v1 Announce Type: new Abstract: Vision-based automation is an excellent candidate for reducing manual labor in greenhouse crop production and phenotyping. However, progress is constrai

applicationsarxiv-cs-cv

Text Template Tokens Are Implicit Semantic Registers in Diffusion Transformers

arXiv:2607.19139v1 Announce Type: new Abstract: Text-to-image diffusion transformers (DiTs) jointly process text and image tokens, yet their internal computation during denoising remains poorly unders

The Anatomy of a Truth Direction: Knowledge-Dependent Dimensionality, a Relational Law, and a Convergent Category Geometry in Small Language Models

model-releasesarxiv-cs-lg

arXiv:2607.16741v2 Announce Type: replace Abstract: Burger et al. (2024) demonstrated that truth representations in large language models are universal across statement polarity but reside within a mu

The Blessing of Dimensionality: How Near-Orthogonality in High-Dimensional Spaces Explains Temporal Portability

model-releasesarxiv-cs-cl

arXiv:2607.20301v1 Announce Type: cross Abstract: Fine-tuning has been widely used to adapt large language models (LLMs) for domain-specific tasks. Parameter efficient fine-tuning (PEFT) methods such

The Blueprint: How Voicify makes AI-enabled ordering a delight for customers

model-releasesgoogle-cloud-ai

Welcome to The Blueprint, a new feature where we highlight how Google Cloud customers are tackling unique and common challenges across industries using the latest AI and cloud technologies. We hope to

The C-index illusion: discrimination without calibration in published survival models

arXiv:2607.19526v1 Announce Type: new Abstract: 'Stop Chasing the C-index when Evaluating Survival Analysis Models' (ICML 2026, Spotlight) argued normatively, on synthetic data, that evaluating surviv

The Chronos Vulnerability: A Taxonomy of Temporal Persistence and Memory-Based Deception in Agentic AI

model-releasesarxiv-cs-ai

arXiv:2607.19433v1 Announce Type: new Abstract: The transition from stateless generative models in artificial intelligence to stateful, autonomous agents represents an architectural evolution that, wh

The Ethics of Autonomous AI Agents for Offensive Security

arXiv:2607.20255v1 Announce Type: cross Abstract: LLM-driven autonomous agents are reshaping offensive security. Unlike traditional penetration-testing tooling -- deterministic, narrowly scoped, and o

safetyarxiv-cs-ai

The first known runaway AI agent - or a very bad marketing stunt?

model-releasessimon-willison

The first known runaway AI agent - or a very bad marketing stunt? Martin Alderson's commentary on the OpenAI accidental cyberattack against Hugging Face includes a couple of details I hadn't considere

The first router built for generative media is here.

model-releasescristobal-valenzuela--x

The first router built for generative media is here. Runway launches AI model router as generative media gets crowded https://techcrunch.com/2026/07/23/runway-bets-on-ai-model-routing-as-generative-me

The Geometry of Learning to Avoid Interventions

arXiv:2602.03825v2 Announce Type: replace Abstract: Human interventions are a common source of supervision in autonomous systems during deployment. Many existing approaches are based on avoiding inter

safetyarxiv-cs-lg

Local Ai

The Giant Hippocampus: From Structural Monoculture to a System of Systems

arXiv:2607.19973v1 Announce Type: new Abstract: AI researchers describe state-of-the-art models as one thing repeated at scale: the Transformer, wired identically for text, pixels, or speech. Neurosci

local-aiarxiv-cs-ai

The JEPA Predictor: A Transferable Operator for Occluded Feature Completion

arXiv:2607.16274v2 Announce Type: replace Abstract: Joint-Embedding Predictive Architectures (JEPAs) train a predictor jointly with their encoder, but downstream deployment discards the predictor and

The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models

model-releasesarxiv-cs-ai

arXiv:2607.20265v1 Announce Type: cross Abstract: Large-scale pretrained language models such as T5 and BERT have demonstrated strong capabilities for generating structured knowledge. However, their p

The Mechanism Matters: When Knowledge Graphs Help Reinforcement Learning

arXiv:2607.19616v1 Announce Type: new Abstract: Knowledge graphs (KGs) are widely used to inject prior knowledge into reinforcement learning (RL), yet the literature is dominated by single-domain, pos

safetyarxiv-cs-lg

The Orthogonalized Read Is a Removable Training Scaffold for Recurrent Memory

arXiv:2607.19390v1 Announce Type: new Abstract: A recent report finds that orthogonalizing the mLSTM memory matrix at read time (five Newton-Schulz iterations, trained through) substantially improves

The PAR dataset: Prostate biopsy whole slide images from an underrepresented Middle Eastern population

arXiv:2512.03854v2 Announce Type: replace Abstract: Artificial intelligence (AI) is increasingly used in digital pathology. Publicly available histopathology datasets remain scarce, and those that do

Applications

The production platform for open-weight AI inference

applicationstogether-ai-blog

OpenAI has updated its inference platform to give users full control over performance, cost, and quality without building their own stack—models go live in minutes and support multiple deployments beh

The Quadrilateral Loss: Additivity as a Measurable Behavior of Dense Neural Networks

arXiv:2607.20201v1 Announce Type: cross Abstract: Additive models buy interpretability by forbidding feature interactions, a constraint that neural instantiations enforce architecturally. We introduce

researcharxiv-cs-ai

The Two-Process Theory of Machine Self-Report

arXiv:2607.20082v1 Announce Type: new Abstract: Language models are increasingly asked to self-report, informing safety evaluations, public understanding, and model-welfare debates. Yet their reports

safetyarxiv-cs-cl

The World Model Remembers, the Actor Forgets: Dream Rehearsal for Continual Model-Based RL

model-releasesarxiv-cs-ai

arXiv:2607.19749v1 Announce Type: cross Abstract: Model-based reinforcement-learning agents of the DreamerV3 family forget catastrophically when trained on task sequences, even when an unbounded repla

Theory-to-Practice Gap for Neural Networks and Neural Operators

arXiv:2503.18219v2 Announce Type: replace Abstract: This work studies the sampling complexity of learning with ReLU neural networks and neural operators. For mappings belonging to relevant approximati

Think Sparse, Predict Dense: Continuous Thought Machines for Image Super-Resolution

model-releasesarxiv-cs-cv

arXiv:2607.18856v1 Announce Type: new Abstract: Continuous Thought Machines introduce an internal temporal dimension in which neuron-level histories and synchronization-derived representations evolve

Thoughtful essay on employment from @Anthropic’s @PeterMcCrory, endorsed by Google DeepMind’s @alexolegimas. I tend also agree with most of …

Thoughtful essay on employment from @Anthropic’s @PeterMcCrory, endorsed by Google DeepMind’s @alexolegimas. I tend also agree with most of it, which is why I have consistently suggested that a jobapo

safetygary-marcus--x