Search: “engineering”

Symbolic Attack Chain Generation from Atomic Red Team Techniques: An Empirical Study of Predicate Representation Granularity

arXiv:2608.00143v2 Announce Type: replace-cross Abstract: Automated attack chain generation is critical for modern cybersecurity, yet manual construction fails to scale as adversary behaviors expand.

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Model Releases

TeXFix-Bench: An Empirically Grounded Multi-Format Benchmark for LLM-Based Document Source Repair

DGX agent

arXiv:2608.07617v1 Announce Type: new Abstract: Scientific and technical writing depends on markup sources that must compile: LaTeX, Typst, and Markdown pipelines fail on missing delimiters, mismatche

model-releasesarxiv-cs-ai

11 Aug 2026

Agents

The Capability Ladder: A Curriculum-Modernization Framework for Workforce Readiness in the AI Era

arXiv:2608.07779v1 Announce Type: new Abstract: Artificial intelligence is changing the task composition of computing work faster than curricula and training typically adapt. This is a curriculum-fram

agentsarxiv-cs-ai

The Theory of Strategic Evolution: Games with Endogenous Players and the Seven Laws of Strategic Replicators

arXiv:2512.07901v4 Announce Type: replace-cross Abstract: Von Neumann founded both game theory and the theory of self-reproducing automata, but the two programs never merged. Rational players do not c

Tools to Explain Neural Networks for Power System Dynamics

arXiv:2608.08048v1 Announce Type: cross Abstract: This paper presents, for the first time in power systems literature to our knowledge, analytical tools to explain the training performance of machine

Local Ai

Weather- and Location-Aware Agentic Dining Recommendation: Leveraging LLM World Knowledge for Region-Sensitive Contextual Reasoning

arXiv:2608.07593v1 Announce Type: cross Abstract: Context-aware recommender systems have long recognized that factors such as location, time, and weather shape where and what people choose to eat. Exi

local-aiarxiv-cs-ai

Local Ai

A MARL Centered Reference Architecture for Large Language Model Augmentation in Smart Manufacturing

arXiv:2608.07148v1 Announce Type: new Abstract: Modern manufacturing imposes six coupled demands on adaptive control: local decisions with global consequences, partial observability, nonstationarity,

local-aiarxiv-cs-ai

A Picture is Worth a Thousand Tokens: How Vision Language Models Cut AI Energy Costs While Improving Accuracy

arXiv:2608.07427v1 Announce Type: new Abstract: LLM inference accounts for over 90% of AI operational energy, scaling directly with input token count---a critical inefficiency for telecom network anal

ArchEGraph: A Large-Scale Graph Dataset for Geometry-Topology-Physics Aligned Building Energy Modeling

model-releasesarxiv-cs-lg

arXiv:2608.06772v1 Announce Type: new Abstract: Accurate estimation of building energy use is essential for achieving carbon neutral and sustainable buildings. To better understand the influence of de

Beyond Starry Night: Shortcut-Aware Control-State Planning for Artist-Grounded Text to Image Generation

arXiv:2608.06751v1 Announce Type: cross Abstract: Artist-grounded image generation requires more than appending an artist name to a prompt. Image models often respond to artist names through canonical

Applications

Curriculum as Code: An AI-Assisted Architecture for Instructional Design in STEM Education

arXiv:2608.07364v1 Announce Type: new Abstract: Contribution: This paper presents a six-phase AI-assisted instructional design architecture based on the Curriculum as Code paradigm, integrating Genera

applicationsarxiv-cs-ai

Density-Functional Excited-State Gradients and Nonadiabatic Couplings on a Consumer GPU from a Contraction-DAG

arXiv:2608.06536v1 Announce Type: cross Abstract: Nonadiabatic dynamics needs an excited-state gradient and an interstate nonadiabatic coupling matrix element (NACME) at every nuclear geometry, and a

safetyarxiv-cs-lg

Local Ai

Dual-Node NVIDIA DGX Spark over Tailscale: A Remote-Access Testbed for Distributed LLM Training and Cyber-Threat-Intelligence Fine-Tuning

arXiv:2608.07226v1 Announce Type: cross Abstract: Compact AI systems make local language-model experimentation increasingly accessible, yet practical evidence for multi-node training on desktop-class

local-aiarxiv-cs-lg

DynaCrys: Crystal Generation with Dynamic Space-Group Diffusion

arXiv:2608.07401v1 Announce Type: cross Abstract: The search for new crystalline materials spans an enormous compositional and structural space. Generating candidates in this space requires jointly mo

researcharxiv-cs-lg

Evaluating Useful Surrogate Models for Configuration Tuning Beyond Accuracy: A Fitness Landscape Analysis Perspective

arXiv:2509.21945v2 Announce Type: replace-cross Abstract: To efficiently tune configuration for better software system performance (e.g., latency) at the deployment and maintenance stage, many tuners

Georeferencing Non-Gazetteered Place Names using Biological Specimen Records

arXiv:2608.06884v1 Announce Type: cross Abstract: Biological specimen records collected by natural history institutions constitute a rich source of temporal geographic knowledge, capturing biodiversit

Stockmark-Nemotron-3-Nano-Omni-JapanDocReader: Structured Document Parsing via Capability Injection and Forgetting Control

model-releasesarxiv-cs-cl

arXiv:2608.06758v1 Announce Type: new Abstract: We present Stockmark-Nemotron-3-Nano-Omni-JapanDocReader, a Japanese document understanding model built from Nemotron-3-Nano-Omni-30B-A3B-Reasoning-BF16

Surg-UniWorld: A Unified Surgical World Model with Multimodal Control Experts

arXiv:2608.06770v1 Announce Type: new Abstract: Controllable surgical world models can provide a generative foundation for surgical artificial intelligence and simulation by synthesizing realistic ins

Applications

Taxonomy-Driven Analysis of Open-Source AI Risk Mitigation Tools

arXiv:2608.07446v1 Announce Type: cross Abstract: Rapid adoption of large language models (LLMs) in enterprise settings has introduced operational, security, and governance risks. As generative AI app

applicationsarxiv-cs-ai

Winning by Peeking: Unenforced Budgets and Test-Set Selection Inflate Short-Budget AutoML Comparisons

arXiv:2608.07303v1 Announce Type: new Abstract: Comparisons between AutoML systems at short time budgets -- tens of seconds rather than hours -- are common in tool READMEs and workshop papers, and the

Agentic self-driving microscopy benchmarks support qualification but do not necessarily generalize to unseen tasks

arXiv:2608.05266v1 Announce Type: new Abstract: Large language model agents are increasingly being developed to control a wide range of scientific characterization tools including microscopes and sync

An Emerging Retail Portfolio Management Application: Personalized, Tax-Aware Reinforcement Learning with Natural Language Goals

arXiv:2608.05255v1 Announce Type: cross Abstract: Retail investors lack access to the kind of personalized, tax-aware portfolio management that institutional clients take for granted -- existing robo-

Autonomous Learning From Success and Failure: Goal-Conditioned Supervised Learning with Negative Feedback

arXiv:2509.03206v2 Announce Type: replace-cross Abstract: Learning from reward functions and imitation learning of demonstrations are the two principal approaches for training autonomous systems that

Agents

Computationally Efficient Collaborative Communication Via Regularity-Based Coarsening

arXiv:2608.05327v1 Announce Type: cross Abstract: Our results show that the existence of a short high-utility protocol already suffices for efficient communication. In particular, in a game with n pos

agentsarxiv-cs-lg

Counterfactual Analysis via Large Language Models

arXiv:2608.05367v1 Announce Type: new Abstract: Counterfactual analysis aims to predict potential outcomes under hypothetical scenarios, offering valuable insights for decision-making. This paper inve

EqDeepRx: Learning a Scalable and Interference Mitigating MIMO Receiver

arXiv:2602.11834v2 Announce Type: replace-cross Abstract: While machine learning (ML)-based receiver algorithms have received a great deal of attention in the recent literature, they often suffer from

researcharxiv-cs-lg

EvoHarness-RL: Learning Self-Evolving Runtime Harness for Long-Horizon LLM Agents

arXiv:2608.05446v1 Announce Type: cross Abstract: Long-horizon LLM agents increasingly rely on external execution support to maintain state, track progress, invoke tools, verify outcomes, and reuse ex

safetyarxiv-cs-cl

FI-TW: An Open Train-Weather Dataset for Railway Delay Analysis in Finland

arXiv:2601.16592v2 Announce Type: replace-cross Abstract: Train delays result from complex interactions between operational, technical, and environmental factors. While weather impacts railway reliabi

From Economic Agents to Agentic Economies: A Systems Blueprint for Economic World Models

arXiv:2608.06020v1 Announce Type: new Abstract: Economic World Models (EWMs) are generative economic models that simulate how economies evolve from within by modeling heterogeneous agents, their belie

Grounded Well-Condition Anomaly Detection on the Volve Field: Constructed Labels, a Baseline, and a Dual-Head Model

arXiv:2608.05685v1 Announce Type: new Abstract: Most public benchmarks for machine-condition monitoring come from test rigs, where faults are induced on purpose and every event is known. Real producti

Hardware

IcFuzz: Fuzzing Isaac Sim with Semantic Stage Guidance and Multi-level Mutation

arXiv:2608.06088v1 Announce Type: new Abstract: Robotics simulators serve as a foundational infrastructure for embodied AI, facilitating safe and scalable robotic system development. NVIDIA Isaac Sim

hardwarearxiv-cs-ro

In-Context VLA: Endowing Vision-Language-Action Models with Language via In-Context Post-Training and Agentic Tool Use

arXiv:2608.05738v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have become the dominant recipe for generalist manipulation, yet they are almost universally trained by behavior clo

safetyarxiv-cs-ro

Agents

Learning Globally Reusable Skills for Coding Agents

arXiv:2608.06153v1 Announce Type: cross Abstract: Automated skill evolution enables Large Language Model (LLM) agents to continuously improve without expensive retraining. However, existing approaches

agentsarxiv-cs-ai

MIRA: A Modular Open-Source Micro-UAV for Indoor Research

arXiv:2607.11785v2 Announce Type: replace Abstract: Indoor robotics research increasingly uses micro-UAV platforms whose airframes, electronics, and control software are open to modification. Off-the-

safetyarxiv-cs-ro

OmniMech: All-in-one Multimodal Mechanical Benchmark for 3D Reconstruction

model-releasesarxiv-cs-cv

arXiv:2608.05539v1 Announce Type: new Abstract: Recent vision-language models (VLMs) can generate executable CAD programs from images, but existing methods mainly target coarse, general-purpose 3D obj

Ordered Diffusion for 3D Human Registration

arXiv:2608.05804v1 Announce Type: new Abstract: 3D human registration has historically been treated as a regression task, assuming a unique ground-truth alignment exists between the template and an in

safetyarxiv-cs-cv

Posture and Sustainment Optimization Under Adversarial Uncertainty

arXiv:2608.05256v1 Announce Type: new Abstract: Pre-commitment posture, the assignment of military assets to theater locations before conflict scenarios resolve, is a critical and formally unsolved pr

Predicting Social Media User Actions: A Hybrid Approach for Common and Rare Behavior Prediction on Bluesky

arXiv:2511.17241v2 Announce Type: replace Abstract: Understanding and predicting user behavior on social media platforms is crucial for content recommendation and platform design. While existing appro

researcharxiv-cs-cl

Tutorials

Reinforcing Action Policies by Prophesying

arXiv:2511.20633v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) policies excel in aligning language, perception, and robot control. However, most VLAs are trained purely by imitation,

tutorialsarxiv-cs-ro

TAU-Bench: From Anomaly Instance Tracking to Fine-Grained Video Anomaly Understanding

model-releasesarxiv-cs-cv

arXiv:2608.05699v1 Announce Type: new Abstract: Humans understand anomalous events through a coherent perceptual process in which they identify the focal instance, follow its behavior as the event unf

Training a Conditioned Video Game Agent on a VLM Annotated Dataset

arXiv:2608.05954v1 Announce Type: new Abstract: Reinforcement Learning (RL) is a powerful but far from easy-to-use technique for policy learning. In the specific case of video games, access to the gam

A Unified Model for Cross-Domain Clone Detection via Model Merging

arXiv:2608.04215v1 Announce Type: cross Abstract: The growing diversity of code clone types, from syntactic copies to cross-language semantic clones to AI-generated duplicates, has created a fragmenta

Hardware

An Explainable LLM Agent Layer for Open-World Anomaly Detection in Oil Wells

arXiv:2608.04041v1 Announce Type: new Abstract: Open-World Learning (OWL) pipelines for oil well anomaly detection have recently been shown to combine autoencoder-based detection, multiclass classific

hardwarearxiv-cs-lg

Argus: A General-Purpose Agentic Runtime for Long-Horizon Reasoning

arXiv:2608.05144v1 Announce Type: new Abstract: Long-horizon reasoning requires an agentic runtime that can persist when evidence supports its current approach and pivot when measurements reveal failu

CoCo-IR: Contextual Composed Image Retrieval

model-releasesarxiv-cs-cv

arXiv:2608.05149v1 Announce Type: new Abstract: Current instruction-based image retrieval systems are powerful but limited to single-turn interactions, failing to capture the iterative nature of compl

Continual-Learning Physics-Informed Neural Networks for Parameterized Partial Differential Equations

model-releasesarxiv-cs-lg

arXiv:2608.04778v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) incorporate governing equations into neural-network training and can approximate PDE solutions without requirin

DAC-Pose: Dual-Agent Collaborative Framework for Pose-Guided Human Generation

arXiv:2608.04622v1 Announce Type: new Abstract: AI agents have emerged as a powerful new paradigm in generative image synthesis, enabling systems to perform complex semantic reasoning rather than pass

safetyarxiv-cs-cv

Diagnosing Tool-Selection Reasoning in LLM Agents with Canary Tools

arXiv:2608.04719v1 Announce Type: new Abstract: Agent evaluations tell us that a model picked the wrong tool, but rarely why. We introduce canary tools: diagnostic probe tools planted in an agent's Mo