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Claude is an incredible coding agent. I use it a lot. (Also Codex and start checking Cursor again). But I’m not convinced the AI-native SDLC…

model-releasesitamar-friedman--x

Claude is an incredible coding agent. I use it a lot. (Also Codex and start checking Cursor again). But I’m not convinced the AI-native SDLC is the existing SDLC with a magical Claude wand waved over

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Model Releases

Eluna: An Agentic LLM System for Automating Warehouse Operations with Reasoning and Task Execution

DGX agent

arXiv:2607.08960v2 Announce Type: replace-cross Abstract: Warehouse operations are governed by Standard Operating Procedures (SOPs) that encode complex, multi-system decision logic, which must be exec

model-releasesarxiv-cs-ai

26 Aug 2026

Event-Based Motion Estimation via Oriented Distance Fields

model-releasesarxiv-cs-cv

arXiv:2608.24223v1 Announce Type: new Abstract: Event-based motion estimation is central to tasks that demand high temporal resolution and robustness to fast motion. Existing methods typically rely on

Orchestration is the new challenge for CX in the age of AI agents

Presented by Tata Communications Enterprises are deploying AI agents, voice AI, and automation across messaging, voice, and digital channels faster than the architecture meant to support it. Most of t

safetyventurebeat-ai

Agents

Rebuild Dossier: Mechanically-Enforced Specs for Agentic App Rebuilds, and What Model-Tier Failures Reveal

arXiv:2608.23616v1 Announce Type: cross Abstract: An AI agent's rebuild is only as good as the process that produced it. Prior work found that once a model is strong enough, a multi-agent rebuild pipe

agentsarxiv-cs-ai

Stabilizing Temporal Difference Learning via Implicit Stochastic Recursion

arXiv:2505.01361v3 Announce Type: replace Abstract: Temporal difference (TD) learning is a foundational algorithm in reinforcement learning (RL). For nearly forty years, TD learning has served as a wo

safetyarxiv-cs-lg

Using OKF with Knowledge Catalog to serve context for agents

model-releasesgoogle-cloud-ai

We continue to iterate on the Open Knowledge Format (OKF), an open specification that formalizes the LLM-wiki pattern into a portable, interoperable format. But a big question remains: How can you sha

A Modular Multitask Reasoning Framework Integrating Spatio-temporal Models and LLMs

arXiv:2506.20073v2 Announce Type: replace-cross Abstract: Spatio-temporal data mining plays a pivotal role in informed decision making across diverse domains. However, existing models are often restri

As-Rigid-As-Possible Regularization for Implicit Surfaces

arXiv:2608.15933v1 Announce Type: cross Abstract: Implicit surface representations have regained popularity because of their use in machine learning. A common component in optimization is regularizati

researcharxiv-cs-cv

Expert-level vision-language foundation model for real-world radiology and comprehensive evaluation

model-releasesarxiv-cs-cv

arXiv:2409.16183v2 Announce Type: replace Abstract: Radiology is a vital and complex component of modern clinical workflow and covers many tasks. Recently, vision-language (VL) foundation models in me

MOCLIP: A Foundation Model for Large-Scale Nanophotonic Inverse Design

arXiv:2511.18980v2 Announce Type: replace-cross Abstract: Foundation models (FM) are transforming artificial intelligence by enabling generalizable, data-efficient solutions across different domains f

Now introducing Gemini Enterprise for Legal

model-releasesgoogle-cloud-ai

Few professions are as exacting as the practice of law. A team reviewing a contract or building a case works inside strictly privileged information, firm-specific playbooks, and a body of law that cha

Precision-Aware Variable Bit Processing Elements for Hardware-Efficient Systolic Array Designs

arXiv:2608.22378v1 Announce Type: cross Abstract: Systolic arrays (SAs) have emerged as prominent hardware accelerators for matrix operations in deep learning, while floating point number formats enab

Seismic Acoustic Impedance Inversion Framework Based on Conditional Latent Generative Diffusion Model

arXiv:2506.13529v2 Announce Type: replace-cross Abstract: Seismic acoustic impedance plays a crucial role in lithological identification and subsurface structure interpretation. However, due to the in

Towards insect-like distributed proprioception in actuators and appendages for flapping-wing insect-scale aerial robots

arXiv:2608.21699v1 Announce Type: new Abstract: Modern flapping-wing insect-scale air vehicles display agility similar to that of their insect counterparts; however, these impressive maneuvers are onl

researcharxiv-cs-ro

What is an intelligent system?

arXiv:2009.09083v4 Announce Type: replace-cross Abstract: The term intelligent system has emerged in the field of information technology as a category of computer systems derived from successful appli

Amortized Bandwidth Learning for Kernel Density Estimation under Logarithmic Score

arXiv:2608.20445v1 Announce Type: new Abstract: Kernel density estimation converts finite samples into probability densities, but its performance depends critically on bandwidth selection. Classical s

Benchmarking Patent Drafting from Inventor-Style Disclosures

model-releasesarxiv-cs-cl

arXiv:2608.21249v1 Announce Type: new Abstract: While recent large language models (LLMs) have achieved promising results on individual patent drafting tasks, they fundamentally fail to investigate th

MM-ToolSandBox: A Unified Framework for Evaluating Visual Tool-Calling Agents

arXiv:2607.11818v2 Announce Type: replace-cross Abstract: We introduce MM-ToolSandBox, a benchmark and evaluation framework for visually grounded tool-calling agents. The framework provides a stateful

One Hierarchy, Two Systems: Semantic Product IDs for Discovery-Surface Ranking and Search-Page Query Reformulation

arXiv:2608.20640v1 Announce Type: cross Abstract: Multi-merchant e-commerce catalogs contain equivalent and related products under different merchant-scoped identifiers, fragmenting behavioral evidenc

Query Efficient Structured Matrix Learning

arXiv:2507.19290v2 Announce Type: replace-cross Abstract: We study the problem of learning a structured approximation (low-rank, sparse, banded, etc.) to an unknown matrix A given access to matrix-vec

Scalable Distributed Simulation-Based Testing for Automated Driving Systems

arXiv:2608.20904v1 Announce Type: new Abstract: Virtual scenario-based testing is a key enabler for validating automated driving systems (ADS) and intelligent transport systems (ITS). However, executi

safetyarxiv-cs-ro

SPD Matrix Learning for Neuroimaging Analysis: Perspectives, Methods, and Challenges

arXiv:2504.18882v3 Announce Type: replace-cross Abstract: Neuroimaging provides essential tools for characterizing brain activity, structure, and connectivity through modalities that capture complemen

Uncertainty propagation in auto-regressive random neural network models

arXiv:2608.20483v1 Announce Type: cross Abstract: We develop analytical and particle-based methods for uncertainty propagation in random neural network models, where both the inputs and network parame

Adaptive Probabilistic Shielding by Learning MDPs for Safe Reinforcement Learning

arXiv:2608.19836v1 Announce Type: cross Abstract: Probabilistic shielding is a technique for safe reinforcement learning (RL). Typically, a static observer -- called the shield -- constrains the learn

safetyarxiv-cs-ai

Composition-Driven Phase Evolution in Sm-Doped BiFeO3 via Latent-Field Reconstruction of Atomically Resolved STEM Data

arXiv:2608.19544v1 Announce Type: cross Abstract: Functionalities of ferroelectric materials are governed by the spatial organization and coupling of polarization, strain, lattice rotation, and struct

DeltaML-Bench: Evaluating Machine Learning Agents on Real-World Research Repositories

arXiv:2608.19653v1 Announce Type: cross Abstract: Autonomous agents for machine learning experimentation must navigate heterogeneous repositories, repair training pipelines, and evaluate candidate imp

Symmetric Lyapunov Subcenter Manifolds for Periodic Regulation of Mechanical Systems

arXiv:2505.13064v4 Announce Type: replace-cross Abstract: Multi-body mechanical systems have rich internal dynamics, whose solutions can be exploited as energy-efficient control targets. Yet, solution

researcharxiv-cs-ro

The impact of feature engineering and an optimisation framework for ocean colour machine learning

arXiv:2608.19899v1 Announce Type: cross Abstract: Machine learning (ML) is widely used for the development of ocean colour algorithms, but most studies focus on model parameter training and hyperparam

Agents

A Comprehensive Review of Large Language Models for Nanophotonics: From Surrogate Modeling to Autonomous Design

arXiv:2608.18279v1 Announce Type: cross Abstract: Metasurfaces have revolutionized the development of photonic devices by enabling unprecedented precision in light manipulation. However, their design

agentsarxiv-cs-lg

Local Ai

A Real-Time Tsetlin Machine-based Non-intrusive Load Monitoring System on MCUs

arXiv:2608.18780v1 Announce Type: new Abstract: Non-Intrusive Load Monitoring (NILM) systems estimate individual appliance energy consumption from a single aggregate meter, without requiring separate

local-aiarxiv-cs-lg

A systematic review of machine learning techniques to address diagnosis and treatment of autism: challenges and opportunities

arXiv:2608.18188v1 Announce Type: cross Abstract: Autism spectrum disorder (ASD) is a developmental disability characterized by challenges in social interaction and communication. As the causes of ASD

Continuous-Time Reinforcement Learning for Controlled Hawkes Jump-Diffusions

arXiv:2608.19151v1 Announce Type: new Abstract: We study stochastic control of multivariate Hawkes-driven stochastic differential equations with machine learning algorithms in a non-Markovian setting.

safetyarxiv-cs-lg

Debiased Inference for AI-Generated Data without Gold-Standard Labels: Identification via Multiple Imperfect Measurements

arXiv:2608.18294v1 Announce Type: cross Abstract: An increasing number of scholars use AI to measure variables they subsequently include in downstream analyses. Although AI-measured variables are ofte

safetyarxiv-cs-ai

Escaping Local Minima Provably in Non-convex Matrix Sensing: A Deterministic Framework via Simulated Lifting

arXiv:2602.05887v3 Announce Type: replace Abstract: Low-rank matrix sensing is a fundamental yet challenging nonconvex problem whose optimization landscape typically contains numerous spurious local m

Expanding Google Antigravity for enterprise customers

model-releasesgoogle-cloud-ai

Since announcing Google Antigravity in Gemini Enterprise Agent Platform at I/O in May, we’ve heard helpful feedback from our customers. Your developers want easy access to coding agents across surface

Local Ai

[MASSIVE TINY RELEASE] - Supra2-Medium-Base - a tiny 25M parameters model competing heavily with our previous 50M model!

Hey guys! Supra2-Medium is finally out! It's a 25M parameters qwen3 architecture model trained entirely from scratch (on our new rig: RTX 5060 Ti 16GB + the new RTX 5060 8GB!). Here's how it competes

local-air-localllama

Tensor Field Models

arXiv:2608.18808v1 Announce Type: new Abstract: This paper introduces Tensor Field Models (TFMs), realization-level Mathematical Structures in which a learned Operator maps a product of admissible com

Local Ai

AISA: AI Safety Assistant Framework for Continuous Improvement of Highway Construction

arXiv:2608.17184v1 Announce Type: new Abstract: Job Safety Analysis (JSA) and pre-task planning can benefit from prior incident records, yet historical accident data is often stored as unstructured na

local-aiarxiv-cs-cl

Fourth-Moment Geometry of Rademacher Sums

arXiv:2608.17802v1 Announce Type: new Abstract: Let arepsilon_1,ldots,arepsilon_n be independent Rademacher signs and let a=(a_1,ldots,a_n)inR^n satisfy the normalization below. For the normalized Rad

Gradient Heterogeneity Complements Hessian Heterogeneity in Transformer Optimization

arXiv:2502.00213v5 Announce Type: replace-cross Abstract: Transformers are difficult to optimize with stochastic gradient descent (SGD) and largely rely on adaptive optimizers such as Adam. Despite ex

Hardware

Great paper if you are building production-grade agents. It's a good way to understand what is actually incurring costs in your agents, whic…

Great paper if you are building production-grade agents. It's a good way to understand what is actually incurring costs in your agents, which involve more complex components and decisions. This works

hardwaredair-ai--x

It was great to be back at @bloomberg studios to chat with @TimStenove1g. We covered quite a bit, but there's one thread worth amplifying fo…

It was great to be back at @bloomberg studios to chat with @TimStenove1g. We covered quite a bit, but there's one thread worth amplifying for founders: the growing importance of having a non-consensus

researchyann-lecun--x

Solving nonconvex Hamilton--Jacobi--Isaacs equations with PINN-based policy iteration

arXiv:2507.15455v3 Announce Type: replace-cross Abstract: We propose a mesh-free policy iteration framework that combines classical dynamic programming with physics-informed neural networks (PINNs) to

safetyarxiv-cs-ai

Tutorials

Without journalists, there is no journalism: the social dimension of generative artificial intelligence in the media

arXiv:2608.17017v1 Announce Type: cross Abstract: The implementation of artificial intelligence techniques and tools in the media will systematically and continuously alter their work and that of thei

tutorialsarxiv-cs-ai

A multi-center analysis of deep learning methods for video polyp detection and segmentation

arXiv:2603.04288v2 Announce Type: replace Abstract: Colonic polyps are well-recognized precursors to colorectal cancer (CRC), typically detected during colonoscopy. However, the variability in appeara

researcharxiv-cs-cv

18 Aug 2026

Balancing Optimality and Diversity: Human-Centered Decision Making through Generative Curation

arXiv:2409.11535v3 Announce Type: replace Abstract: Many decision-support systems recommend actions by optimizing measurable objectives, even when a human decision-maker retains final authority and co

safetyarxiv-cs-lg

18 Aug 2026

Deep learning-based computed tomography (CT) derived body composition classifier for colorectal cancer patients

arXiv:2608.15712v1 Announce Type: cross Abstract: Background: Accurate body composition analysis using Computed Tomography (CT) scans is essential for assessing skeletal muscle area (SMA) and skeletal