Search: “engineering”

ORGAN: Object-Centric Representation Learning using Cycle Consistent Generative Adversarial Networks

arXiv:2603.02063v2 Announce Type: replace Abstract: Although data generation is often straightforward, extracting information from data is more difficult. Object-centric representation learning can ex

applicationsarxiv-cs-cv

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Physical AI Governance: From Theory to Practice Across Life Cycle

DGX agent

arXiv:2607.22877v1 Announce Type: new Abstract: With the emergence of Physical AI, artificial intelligence is extending beyond screen-based applications to embodied systems that perceive, interact wit

safetyarxiv-cs-ai

28 Jul 2026

Physics-Guided Generative AI for Property-Targeted 3D Porous Media Design

arXiv:2607.24274v1 Announce Type: cross Abstract: Inverse design of three-dimensional porous media is central to applications in filtration, catalysis, energy storage, fuel cells, thermal management,

Real2Sim2Real for Vision-Language-Action Manipulation: An AMD ROCm-Based Pipeline

arXiv:2607.22997v1 Announce Type: cross Abstract: Physical AI -- the integration of large vision-language-action (VLA) models with embodied agents that act in the real world -- has emerged as the next

Rendering on Real Silicon: GPU Render-Timing as a Passive, AI-Resistant CAPTCHA Signal

arXiv:2607.23389v1 Announce Type: cross Abstract: Conventional CAPTCHAs pose puzzles that modern AI systems increasingly solve, while behavioral and cryptographic-attestation defenses carry privacy or

hardwarearxiv-cs-lg

Separating Capability from Permission: A Governance Framework for Agentic AI Autonomy Levels

arXiv:2607.23438v1 Announce Type: new Abstract: As AI systems increasingly exhibit agentic behavior, discussions of autonomy often conflate what systems are technically capable of doing with what they

SetGo: Metadata Readiness for Scientific AI Datasets

arXiv:2607.22677v1 Announce Type: cross Abstract: Scientific datasets intended for AI use require both computational readiness for model training and metadata readiness for discovery, sharing, and reu

Simulating Tenant Responses to Energy Policy Interventions with Transaction-Cost-Aware LLM Age

model-releasesarxiv-cs-ai

arXiv:2607.24341v1 Announce Type: new Abstract: Recent studies use Large language models (LLMs) to simulate human opinions and decisions by prompting models with demographic, attitudinal, or persona-b

Source-Aware Reranking for Retrieval-Augmented Generation: A Reliability Prior Approach

arXiv:2607.22584v1 Announce Type: new Abstract: Standard Retrieval-Augmented Generation pipelines rank retrieved documents by semantic similarity alone, without accounting for source provenance or cre

Statistically Supported LLM Ingredient and Recipe Data Collection in Computational Nutrition

arXiv:2607.23273v1 Announce Type: cross Abstract: Computational nutrition needs precise ingredient data, but current databases are incomplete, inconsistent, and built for human reference rather than a

Stochastic Counterdiabatic Driving via Biorthogonal Liouvillian Eigenmodes

arXiv:2607.24393v1 Announce Type: cross Abstract: Finite-time driving of stochastic systems generates excess dissipation, causing the evolving probability distribution to lag behind the instantaneous

researcharxiv-cs-lg

Task-Conditional Faithfulness Auditing of Multimodal LLMs for Grid Diagnosis

arXiv:2607.24539v1 Announce Type: new Abstract: Multimodal large language models (LLMs) can combine topology, measurements, and incident text for grid diagnosis, yet answer accuracy does not establish

The Illusion of Secure LLM Code: Closing the Security Gap via Iterative Reprompting

arXiv:2607.23710v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly integrated into software development workflows, yet their ability to autonomously generate secure authen

applicationsarxiv-cs-ai

Transfer Learning Architectures for Scalable Multi-Fidelity Bayesian Optimization

model-releasesarxiv-cs-lg

arXiv:2607.23404v1 Announce Type: new Abstract: Self-driving laboratories increasingly rely on multi-fidelity Bayesian optimization (MFBO) to balance cheap, approximate evaluations against scarce, exp

UAV-ON: A Benchmark for Open-World Object Goal Navigation with Aerial Agents

model-releasesarxiv-cs-cv

arXiv:2508.00288v5 Announce Type: replace-cross Abstract: Aerial navigation is a fundamental yet underexplored capability in embodied intelligence, enabling agents to operate in large-scale, unstructu

Local Ai

VecTree-RAG: An Agentic Retrieval-Augmented Generation Framework Combining Vector and Tree Retrieval for Efficiency and Accuracy

arXiv:2607.23006v1 Announce Type: cross Abstract: Scientific question answering requires a retrieval system to solve two distinct problems: identifying which papers are relevant and locating the suppo

local-aiarxiv-cs-ai

Tutorials

VIPER: Visual In-Context Physics Reasoning for Physically Plausible Video Generation

arXiv:2607.23472v1 Announce Type: new Abstract: Modern video generation models can synthesize visually compelling and temporally coherent clips, yet controlling their physical behavior remains difficu

tutorialsarxiv-cs-cv

Visual Information Extraction from Documents via Classification-Guided Large Vision-Language Models

arXiv:2607.22723v1 Announce Type: new Abstract: Visual information extraction (VIE) from visually rich documents remains challenging due to high layout variability and real-world impairments. Existing

applicationsarxiv-cs-cv

A Unified Framework for Automated Assembly Sequence and Production Line Planning using Graph-based Optimization

arXiv:2512.13219v2 Announce Type: replace Abstract: This paper presents PyCAALP (Python-based Computer-Aided Assembly Line Planning), a framework for automated Assembly Sequence Planning (ASP) and Pro

applicationsarxiv-cs-ro

Automatic Map Density Selection for Locally-Performant Visual Place Recognition

arXiv:2602.21473v3 Announce Type: replace Abstract: A key challenge in translating Visual Place Recognition (VPR) from the lab to long-term deployment is ensuring a priori that a system can meet user-

researcharxiv-cs-cv

Certified in Theory, Broken in Practice: Assumption Gaps in Cryptographic Model Certification

arXiv:2607.21839v1 Announce Type: cross Abstract: Privacy-preserving machine learning auditing protocols allow auditors to assess models for properties such as accuracy or fairness, without revealing

safetyarxiv-cs-lg

From Obligation to Specification: A Survey on Validating EU AI Act Requirements in RE

arXiv:2607.21608v1 Announce Type: cross Abstract: With the EU AI Act entering into force, organizations developing or operating AI systems face new obligations on transparency, risk management, and tr

safetyarxiv-cs-cl

LeAct: Learning to Reason from Expert Actions

arXiv:2607.21856v1 Announce Type: cross Abstract: Modern reasoning models depend on reasoning data, today sourced from human annotations or distilled from stronger LLMs. However, a rich and largely un

RIS-Kernel: A Model-Agnostic Architecture for Long-Context LLM Inference via Sparse Attention

arXiv:2607.21927v1 Announce Type: new Abstract: Full self-attention in large language models scales as O(N^2), which limits long-context document analysis to 65,536 tokens and requires costly GPU clus

hardwarearxiv-cs-lg

SCOPE and SCION: A Benchmark and an Auditable Reference Pipeline for Schema Induction and Fusion from Text

model-releasesarxiv-cs-lg

arXiv:2607.21610v1 Announce Type: cross Abstract: Schema graphs are an upstream bottleneck of schema-grounded information extraction and knowledge graph construction, yet most extraction systems assum

SiPhy: Single-Image Physical Property Reasoning

arXiv:2607.22355v1 Announce Type: new Abstract: Inferring physical properties such as mass, stiffness, and elasticity from a single image is essential for simulation and embodied AI, yet most existing

researcharxiv-cs-cv

Skill Self-Play: Pushing the Frontier of LLM Capability with Co-Evolving Skills

arXiv:2607.22529v1 Announce Type: new Abstract: LLM training is shifting from manual design and annotation to interaction-driven self-evolution. However, existing self-evolutionary methods face a fund

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation

arXiv:2510.04602v4 Announce Type: replace-cross Abstract: Wasserstein barycenters provide a principled approach for aggregating probability measures, while preserving the geometry of their ambient spa

researcharxiv-cs-lg

A Graph Neural Network approach to zero-shot Digital Twins

arXiv:2607.20535v1 Announce Type: cross Abstract: Traditional Predictive Digital Twins often remain geometrically rigid, requiring extensive retraining or fine-tuning whenever the underlying physical

applicationsarxiv-cs-ai

Achieving Text-based Person Retrieval with Any Granularity

model-releasesarxiv-cs-cv

arXiv:2607.21057v1 Announce Type: new Abstract: Text-based person retrieval faces a critical but under-explored challenge: the inherent uncertainty of query granularity in real-world scenarios. This p

Beyond Heavy Log Curation: Perplexity-Based APT Detection via Unsupervised, Context-Augmented Language Models

arXiv:2607.20832v1 Announce Type: cross Abstract: Advanced Persistent Threats (APTs) remain difficult to detect because only a small fraction of events in large-scale logs are attack-related, and inve

Tutorials

Beyond SBDD: Geometric Deep Learning in Polypharmacology and Multi-target Drug Design

arXiv:2607.20550v1 Announce Type: cross Abstract: The traditional 'one drug, one target' paradigm of structure-based drug design (SBDD) frequently proves inadequate for treating multifactorial disease

tutorialsarxiv-cs-ai

Can AI Agents Really Complete RTL-to-GDS? Lessons from Benchmarking Tool-Interactive EDA Workflows

arXiv:2607.17528v3 Announce Type: replace Abstract: Large language model (LLM) agents are extending electronic design automation (EDA) beyond static RTL generation toward long-horizon, tool-interactiv

GPE: Evaluating Robust Evidence Aggregation for Fact Verification under Controllable GEO-Style Poisoning

model-releasesarxiv-cs-ai

arXiv:2607.20730v1 Announce Type: cross Abstract: Large language models increasingly use search tools to retrieve up-to-date information, introducing a new attack surface in which retrieved documents

MedGame: Storytelling Gamification Empowered by Large Language Models for Medical Education

arXiv:2607.21570v1 Announce Type: new Abstract: Large Language Models (LLMs) show promise for medical education, but most existing systems focus on localized interactions such as question answering or

NVIDIA-labs OO Agents: Native Python Object-Oriented Agents

arXiv:2607.20709v1 Announce Type: new Abstract: Traditional agent development is split across prompt templates, tool schemas, callback code, and workflow graphs. We present NVIDIA Object-Oriented Agen

OPTScientist: Multi-Agent Discovery of Typed Optimizer Programs for Transformer Pretraining

arXiv:2607.20486v1 Announce Type: new Abstract: Designing optimizers for modern deep learning remains a challenging scientific problem, requiring the joint consideration of optimization geometry, stat

SafeStep: AI-powered Travel Assistance for Elderly People with Frailty or Dementia

arXiv:2607.21156v1 Announce Type: new Abstract: More than a million people in the UK suffer from frailty or dementia, which severely compromise their ability to travel in urban environments. This pape

safetyarxiv-cs-ai

Sample-Efficient Learning from Agent Experience

arXiv:2607.21051v1 Announce Type: new Abstract: Real-world agent learning is often constrained by costly environment interactions, such as running time-consuming experiments or obtaining human feedbac

agentsarxiv-cs-cl

SANA-Video 2.0: Hybrid Linear Attention with Attention Residuals for Efficient Video Generation

arXiv:2607.21553v1 Announce Type: new Abstract: We introduce SANA-Video 2.0, a hybrid video diffusion transformer instantiated at 5B and 14B scales under a unified architecture. Designed to generate h

hardwarearxiv-cs-cv

Skill-Contracted Agents for Evidence-Aware Materials Literature Analysis

arXiv:2607.20431v1 Announce Type: new Abstract: Materials science literature analysis requires simultaneous attention to composition, processing, characterization, and property relationships, yet conv

agentsarxiv-cs-cl

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

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

Transformer-Assisted LLM-Based Source Code Summarisation: to Enable More Secure Software Development

arXiv:2607.20933v1 Announce Type: cross Abstract: Neural Source Code Summarisation (NSCS) aims to generate natural language summaries of source code to improve developers' and maintainers' understandi

researcharxiv-cs-cl

What Matters for Simulation to Online Reinforcement Learning on Real Robots

arXiv:2602.20220v2 Announce Type: replace-cross Abstract: We investigate what specific design choices enable successful online reinforcement learning (RL) on physical robots. Across 100 real-world tra

applicationsarxiv-cs-ai

WildTrace: Benchmarking Natural Evidence Trails in Long-Context Reasoning

model-releasesarxiv-cs-ai

arXiv:2607.09328v2 Announce Type: replace-cross Abstract: Answering complex questions over long documents frequently requires integrating evidence that the source itself disperses naturally across dis

A Framework of User Experience Principles for Human-AI Agent Interaction in the Workplace

arXiv:2607.19941v1 Announce Type: cross Abstract: As AI agents become integral to business workflows, establishing guiding user experience (UX) principles is crucial for ensuring user trust and succes

23 Jul 2026

A Systematic Evaluation of Traditional Privacy Policy Analysis Tools Against LLMs

arXiv:2607.17075v2 Announce Type: replace-cross Abstract: The advent of LLMs has significantly changed the research on privacy policy and data compliance analysis by enabling tasks that previously req