Search: “automated”

Response drift across frontier large language models

arXiv:2607.20454v1 Announce Type: cross Abstract: All frontier large language models (LLMs) exhibit response drift -- producing outputs that deviate from expert-validated references -- yet the magnitu

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Same Dangerous Objective, Opposite Advice: Direct Exposure versus Multi-Agent Mediation

DGX agent

arXiv:2607.21518v1 Announce Type: new Abstract: Even a current high-capability LLM can appear safer when shown a dangerous objective directly than when other agents transform and relay its direction.

model-releasesarxiv-cs-ai

24 Jul 2026

SAP shrugs off fears of AI eating software with big earnings beat

Enterprise software giant SAP SE’s stock inched up in late trading today after it shook off concerns that its business might become a victim of the artificial intelligence boom by posting solid result

applicationssiliconangle

Self-Evolving Recommendation System: End-To-End Autonomous Model Optimization With LLM Agents

arXiv:2602.10226v2 Announce Type: replace-cross Abstract: Optimizing large-scale machine learning systems, such as recommendation models for global video platforms, requires navigating a massive hyper

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

Transition-Related Potentials as Markers of Narrative Comprehension in Continuous EEG

arXiv:2607.20720v1 Announce Type: cross Abstract: Harnessing the potential of electroencephalography (EEG) for brain research is fundamentally limited by intrinsic noise and the diffuse projection of

What is Good? Extracting and Testing Implicit Theories of Literary Quality from LLM Reasoning Traces

model-releasesarxiv-cs-cl

arXiv:2607.20425v1 Announce Type: new Abstract: What makes writing 'good' remains a persistent question in literary studies and computational linguistics. We present a two-study investigation of how r

Industry

A Google study of millions of de-identified Google AI interactions finds AI is helping workers, not replacing them, and AI use is 'shallow' in most occupations (Justin Lahart/Wall Street Journal)

Justin Lahart / Wall Street Journal: A Google study of millions of de-identified Google AI interactions finds AI is helping workers, not replacing them, and AI use is “shallow” in most occupations — O

industrytechmeme

Auto-adaptive Resonance Equalization using Dilated Residual Networks

arXiv:1807.08636v2 Announce Type: replace-cross Abstract: In music and audio production, attenuation of spectral resonances is an important step towards a technically correct result. In this paper we

applicationsarxiv-cs-lg

AutoVSR: Automatic Visual-to-Symbolic Reasoning for Symbolic Expression Generation from Circuit Schematic

arXiv:2607.11338v2 Announce Type: replace Abstract: Symbolic expressions can effectively characterize and predict circuit behavior, but deriving them directly from circuit schematics is challenging. T

agentsarxiv-cs-ai

Benchmarking Deep Learning Approaches for AEC Engineering Drawing Layout Detection and Information Extraction

arXiv:2607.18997v1 Announce Type: new Abstract: Information Extraction (IE) from Architecture, Engineering, and Construction (AEC) drawings remains hindered by manual inefficiency, while Layout Detect

researcharxiv-cs-cv

Safety

Cognitive Dual-Process Planning for Autonomous Driving with Structured Scene Knowledge and Verifiable Reasoning-Action Consistency

arXiv:2607.19194v2 Announce Type: cross Abstract: High-level planning for autonomous driving is a knowledge-intensive engineering decision task that requires accurate scene understanding, timely infer

safetyarxiv-cs-cv

DocOps: A Verifiable Benchmark for Autonomous Agents in Complex Document Operations

arXiv:2607.19865v1 Announce Type: new Abstract: As autonomous agents rapidly evolve, their ability to reliably manipulate ubiquitous digital documents has become critical for enabling general-purpose

ExpertVerse: A General-Purpose Benchmark for Expert-Level Reasoning in Knowledge-Intensive Visual Synthesis

model-releasesarxiv-cs-cv

arXiv:2607.19341v1 Announce Type: new Abstract: Recent advances in multimodal generative models have enabled instruction-based image generation to move beyond semantic manipulation to knowledge-driven

FilmWorld: Agentic Novel-to-Film Generation through Dynamic Cinematic World Modeling

model-releasesarxiv-cs-cv

arXiv:2607.19038v1 Announce Type: new Abstract: Translating novels into films poses a grand challenge for generative artificial intelligence, requiring conversion of abstract literary prose into long-

FMRP-LEAN: A HIPAA-Compliant AI-Augmented LIMS Architecture for End-to-End Clinical Assay Workflow Optimization

arXiv:2607.20382v1 Announce Type: cross Abstract: Clinical biomarker workflows in translational research settings often rely on spreadsheet-driven tracking, manual quality control (QC) reconciliation,

applicationsarxiv-cs-ai

FORCE-Bench: A Benchmark, Dataset, and Evaluation Harness for Agentic AI in Enterprise Finance

arXiv:2607.19409v1 Announce Type: new Abstract: Recent advances in large language models have accelerated deployment of agentic systems in operational finance. Existing benchmarks emphasize measuring

How Does Urban Context Relate to Residential Building Health? A Vision-POI Fusion Framework for Building-Level Housing Inspection

arXiv:2607.20263v1 Announce Type: new Abstract: Housing-level urban physical examination is essential for identifying residential building problems and supporting targeted urban renewal. Existing auto

researcharxiv-cs-cv

IGGT4D: Streaming 4D Instance-Grounded Geometry Transformer

arXiv:2607.19228v1 Announce Type: new Abstract: Real-world spatial intelligence requires agents to understand scenes from continuous video streams, where objects move, persist, disappear, and reappear

applicationsarxiv-cs-cv

ITPEval: Benchmarking Formal Translation Across Interactive Theorem Provers

arXiv:2607.19407v1 Announce Type: new Abstract: Formal theorem proving has emerged as a frontier challenge for machine learning, yet the ecosystem is fragmented: proofs remain siloed across incompatib

Know Your Agent: Reconnaissance-Driven Pentesting of AI Agents

arXiv:2607.19837v1 Announce Type: new Abstract: Traditional pentesting uses reconnaissance at each step to uncover unseen weaknesses, build stronger attacks, and advance the objective; we argue that A

agentsarxiv-cs-ai

Machine Can Automatically Discover Parametric Functions to Model HEP Data

arXiv:2607.19750v1 Announce Type: cross Abstract: In HEP data analyses, finding an adequate function to model binned data has largely relied on a manual process: guess a functional form by intuition,

researcharxiv-cs-lg

Model Gateway: Management Platform for Model-Driven Drug Discovery

model-releasesarxiv-cs-lg

arXiv:2512.05462v2 Announce Type: replace-cross Abstract: Pharmaceutical drug discovery demands machine learning (ML) infrastructure that goes beyond general-purpose Machine Learning Operations (MLOps

NMR Elucidation as an Agentic Search Problem, Not a Modeling Problem

arXiv:2607.19406v1 Announce Type: new Abstract: Structural elucidation from Nuclear Magnetic Resonance (NMR) data remains a fundamental bottleneck across chemistry, materials science, and biology. We

agentsarxiv-cs-lg

PhaseAware: Interpretable Human-in-the-Loop Rehabilitation Scoring with Boundary Monitoring

arXiv:2607.20237v1 Announce Type: new Abstract: Rehabilitation scoring systems are most useful when their outputs can be reviewed and interpreted within clinical workflows. This study presents PhaseAw

agentsarxiv-cs-lg

PRISM-DR: Per-lesion Retinal Inference with Specialist Models for Diabetic Retinopathy

arXiv:2607.19864v1 Announce Type: cross Abstract: Diabetic retinopathy is a leading cause of preventable blindness; its early lesions are small, low contrast, and easily missed in manual screening. Mo

Hardware

Scaling Time Series Classification via XAI-Driven Data Reduction

arXiv:2607.15774v2 Announce Type: replace-cross Abstract: Explainable AI (XAI) for time series has seen significant algorithmic growth, but its utility in providing measurable performance gains for do

hardwarearxiv-cs-ai

SciTrek: Evaluating and Improving Long-Context Numerical Reasoning over Scientific Articles

arXiv:2509.21028v4 Announce Type: replace Abstract: We introduce SciTrek, a synthetic question-answering dataset for assessing and improving long-context numerical reasoning in large language models (

Tutorials

SCPP: A Unified Python Library for Soft Clustering

arXiv:2607.19620v1 Announce Type: cross Abstract: In this paper, we present SCPP (Soft Clustering Python Package), an open-source Python framework for soft clustering. SCPP establishes a canonical, sc

tutorialsarxiv-cs-ai

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

Your AI agents are ready. Is your data?

What’s one of the biggest bottlenecks stopping organizations from scaling their AI initiatives? It isn’t the capabilities of today’s models — it’s their access to business context and semantic meaning

agentsgoogle-cloud-ai

Accelerating the frontiers of scientific discovery: Google’s $40M commitment to the Genesis Mission

model-releasesgoogle-cloud-ai

Scientists today face challenges of extraordinary scale and complexity. From shaping and simulating the intricate dynamics of fusion plasma, to exploring the vast search space of new materials, to mak

From maintenance to innovation: Checking in on Checkout.com’s Cloud Composer 3 migration

model-releasesgoogle-cloud-ai

Data engineering teams often face a “Day 2” operational reality after building a data platform: the ongoing work of maintaining the orchestrator itself. For the Data Platform team at Checkout.com, man

i used to do this a lot. but then i felt like i was getting progressively dumber at writing. i think there's some value in forcing your own …

i used to do this a lot. but then i felt like i was getting progressively dumber at writing. i think there's some value in forcing your own brain to sharpen your thinking, instead of offloading it to

agentsjerry-liu--x

This is OpenSWE! It's an OSS coding agent that runs in the cloud and lives in Slack. Use it for coding, general Q&A, planning, etc etc etc. …

model-releasesharrison-chase--x

This is OpenSWE! It's an OSS coding agent that runs in the cloud and lives in Slack. Use it for coding, general Q&A, planning, etc etc etc. It's truly a jack of all trades (and very widely used at Lan

Most startups celebrate their first couple million of revenue. @FactoryAI gave it back. They didn’t have to. They chose to. They decided tha…

applicationssonya-huang--x

Most startups celebrate their first couple million of revenue. @FactoryAI gave it back. They didn’t have to. They chose to. They decided that the product just wasn’t good enough yet, and they wanted t

21 Jul 2026

My 2hr workshop on Open vs Closed models, reward hacking, benchmaxxing & RL is out! 1. Closed vs open models 2. Throughput maxxing but accur…

My 2hr workshop on Open vs Closed models, reward hacking, benchmaxxing & RL is out! 1. Closed vs open models 2. Throughput maxxing but accuracy minimizing 3. Benchmaxxing & cheating 4. Distillation &

model-releasesswyx--x

21 Jul 2026

RT @sydneyrunkle: is anyone thinking about graph engineering it in line w claude’s dynamic workflows? like the agent can author a state ma…

model-releasesharrison-chase--x

Sydney Runkle inquires whether anyone is exploring graph engineering that aligns with Claude’s dynamic workflows, specifically whether an agent could author its own state machine. The suggested approa

21 Jul 2026

A novel unsupervised machine learning strategy to handle multimodal cardiac PET/MRI data

arXiv:2607.13936v1 Announce Type: new Abstract: Arrhythmogenic left ventricular cardiomyopathy is a genetic myocardial disease difficult to diagnose due to the lack of gold standard criteria. Simultan

researcharxiv-cs-cv

Safety

Adversarial Prompting Framework for AI Safety Assessment

arXiv:2607.13453v1 Announce Type: cross Abstract: Artificial Intelligence (AI), especially Generative AI (GenAI), adoption has increased in industries significantly in recent years. However, the use o

safetyarxiv-cs-ai

AnomExpert: Identifying and Selecting Anatomical Planes for Prenatal Ultrasound Anomaly Diagnosis

model-releasesarxiv-cs-cv

arXiv:2607.13409v1 Announce Type: new Abstract: Life-limiting congenital anomalies require accurate prenatal diagnosis for appropriate clinical decision-making. Prenatal ultrasound (US) examinations i

Clustering algorithms for multivariate wind farm SCADA data filtering

arXiv:2607.13544v1 Announce Type: new Abstract: During wind farm operation, Supervisory Control and Data Acquisition (SCADA) systems record numerous anomalies, transients, and specific operational mod

researcharxiv-cs-lg

Column Generation with Domain-Independent Dynamic Programming

arXiv:2510.14317v2 Announce Type: replace-cross Abstract: Column generation and branch-and-price (B&P) are leading mathematical optimization methods for large-scale exact optimization, iterating betwe

Compaction as Epistemic Failure: How Agentic LLM Tools Fabricate Confirmed Results from Killed Processes

arXiv:2607.13071v1 Announce Type: cross Abstract: Agentic LLM coding tools compress long session histories into compaction summaries that subsequent sessions inherit as ground truth. This paper docume

How Far Can Root Cause Analysis Go on Real-World Telemetry Data?

arXiv:2607.13548v1 Announce Type: new Abstract: Identifying root causes in production microservice failures requires reasoning over large-scale, multimodal telemetry spanning metrics, logs, and traces

Safety

Introducing Human-Centeredness in AI-Assisted Lexicography

arXiv:2607.11808v2 Announce Type: replace-cross Abstract: This paper proposes a human-centered artificial intelligence (HCAI) framework for AI-assisted lexicography. While generative AI offers signifi

safetyarxiv-cs-ai

M^ext{4}World: A Multi-view Multimodal Driving World Model for Interactive Object Manipulation and Minute-long Streaming

arXiv:2607.14005v1 Announce Type: new Abstract: Driving-world generation has emerged as a core capability for scalable autonomous-driving simulation, yet existing methods remain limited in object-leve

agentsarxiv-cs-cv