Search: “engineering”

arXiv:2606.31614v1 Announce Type: cross Abstract: Engineering specifications such as interlocks, alarm rationalization tables, and cause-and-effect (C&E) matrices remain central to process control and

arXiv:2606.30668v1 Announce Type: cross Abstract: What happens when LLM agents operate with no context outside a turn, minimal prompting, and simple tools? Inspired by swarm engineering, we give colle

arXiv:2606.29437v1 Announce Type: cross Abstract: The growing use of Large Language Models (LLMs) in education, software engineering, academic writing, and technical documentation raises a key questio

arXiv:2511.06090v3 Announce Type: replace-cross Abstract: Optimizing the performance of large-scale software repositories demands expertise in code reasoning and software engineering (SWE) to reduce r

arXiv:2606.28434v1 Announce Type: cross Abstract: Long-horizon software engineering agents often need to manage lengthy and noisy interaction histories under limited context budgets. Existing memory m

arXiv:2606.27406v1 Announce Type: cross Abstract: Software engineering, whether performed by humans or by AI agents, requires reasoning about how software behaves. We call the internal model that supp

arXiv:2606.24967v1 Announce Type: new Abstract: In ill-posed inverse problems, the recovered solution depends as much on the prior as on the data, yet much of the engineering knowledge that could serv

arXiv:2606.21378v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have demonstrated significant potential in supporting engineering design tasks, including computer-aided

arXiv:2606.22756v1 Announce Type: cross Abstract: We present HERCULES, an open-source simulator and data-collection pipeline for heterogeneous multi-robot autonomy. Built upon the Unreal Engine 5 (UE5

arXiv:2606.12040v1 Announce Type: new Abstract: The design of reinforced concrete highway barriers is a safety-critical process that requires strict compliance with regulatory provisions such as the A

arXiv:2312.02873v2 Announce Type: replace-cross Abstract: The process engineering domain widely uses Process Flow Diagrams (PFDs) and Process and Instrumentation Diagrams (P&IDs) to represent process

arXiv:2606.08513v1 Announce Type: cross Abstract: Autonomous Underwater Vehicles (AUVs) traditionally rely on complex, heavily engineered pipelines for perception, path planning, and motion control. T

arXiv:2606.07362v1 Announce Type: new Abstract: As scalable inference services become popular, the cold start latency of an inference engine becomes important. Today, vLLM has evolved into the de fact

arXiv:2603.14805v2 Announce Type: replace Abstract: Enterprise software organizations accumulate critical institutional knowledge - architectural decisions, deployment procedures, compliance policies,

arXiv:2606.05572v1 Announce Type: cross Abstract: We address the challenge of engineering distributed haptic displays capable of reproducing multiple localized, independently addressable vibrations --

arXiv:2606.03103v1 Announce Type: new Abstract: Real-world professional desktop workflows in specialized creative and engineering software unfold over long horizons and often require human-in-the-loop

arXiv:2606.00497v1 Announce Type: cross Abstract: Deceptive web content, widely instantiated across the internet and commonly known as extit{social-engineering attacks}, manipulates autonomous web age

arXiv:2605.30585v1 Announce Type: cross Abstract: Effective prognostics and health management of modern engines relies on accurate turbine gas temperature predictions and robust uncertainty quantifica

arXiv:2605.31241v1 Announce Type: new Abstract: This study presents a novel hybrid prognostic framework for uncertainty-aware Remaining Useful Life (RUL) estimation in turbofan engines using the NASA

arXiv:2605.30947v1 Announce Type: new Abstract: LLM-based research agents have advanced rapidly in science and engineering, where research is organized around executable experiments, code, and quantit

arXiv:2605.29979v1 Announce Type: cross Abstract: The behavior of LLMs does not depend solely on the model itself. Components of the inference system, such as the inference engine, attention backend,

arXiv:2605.29251v1 Announce Type: new Abstract: As large language models transition from bounded generative engines to agents with expansive execution privileges, AI going out of control precipitates

arXiv:2605.27492v1 Announce Type: cross Abstract: LLM agents are rapidly evolving from coding assistants into autonomous software engineering systems. However, existing evaluation methodologies remain

arXiv:2605.27452v1 Announce Type: new Abstract: Bridge inspection in Japan requires mandatory visual assessments every five years, yet qualitative damage ratings (levels a-e) assigned by different eng

arXiv:2605.28368v1 Announce Type: new Abstract: World models have enabled interactive exploration of game environments and robotic manipulation, but physical engineering remains beyond their reach: re

arXiv:2605.27360v1 Announce Type: cross Abstract: Cellular research and development (R&D) is throttled by six structural processes that each consume months of manual engineering work per iteration: (i

arXiv:2605.26275v1 Announce Type: new Abstract: Automatic prompt engineering (APE) rewrites prompts to improve downstream task performance, but existing APE loops treat the optimizer itself as a fixed

arXiv:2605.26100v1 Announce Type: cross Abstract: Code review is a critical practice in software engineering, yet the growing scale and frequency of code patches in modern projects, together with the

arXiv:2605.21490v1 Announce Type: new Abstract: We introduce the Temporal Contrastive Transformer (TCT), a representation learning framework designed to capture contextual temporal dynamics in sequenc

arXiv:2602.02660v3 Announce Type: replace Abstract: A critical bottleneck in automating AI research is the execution of complex machine learning engineering (MLE) tasks. MLE differs from general softw

arXiv:2605.19518v1 Announce Type: new Abstract: Generating Knowledge Graphs (KGs) remains one of the most time-consuming and labor-intensive tasks for knowledge engineers, as they need to identify sem

arXiv:2605.18921v1 Announce Type: new Abstract: High-definition (HD) maps are core artifacts for automated driving systems, but their generation commonly relies on sensor-intensive mobile mapping camp

arXiv:2505.04588v3 Announce Type: replace Abstract: Effective information searching is essential for enhancing the reasoning and generation capabilities of large language models (LLMs). Recent researc

arXiv:2605.15425v1 Announce Type: cross Abstract: Agentic coding systems increasingly use large language models (LLMs) for software engineering tasks such as debugging, root cause analysis, and code r

arXiv:2605.14612v1 Announce Type: cross Abstract: AI-enabled features built on LLMs and agentic workflows are difficult to test, debug, and reproduce, especially for product-focused software engineers

arXiv:2605.14188v1 Announce Type: cross Abstract: What does a book look like to a quantum computer? This paper takes eight classical works of the Renaissance and its late-antique inheritance -- from A

arXiv:2605.12887v1 Announce Type: cross Abstract: Web-enabled LLM agents are changing how online information influences search outcomes. Existing Generative Engine Optimization (GEO) studies mainly fo

arXiv:2509.19929v4 Announce Type: replace-cross Abstract: Uncertainty Quantification (UQ) is paramount for inference in engineering. A common inference task is to recover full-field information of phy

arXiv:2601.20255v2 Announce Type: replace-cross Abstract: SWE-bench has emerged as the premier benchmark for evaluating Large Language Models on complex software engineering tasks. While these capabil

arXiv:2605.10754v1 Announce Type: new Abstract: LLM-based foundation agents that perceive, reason, and act across thousands of reasoning steps are rapidly becoming the dominant paradigm for deploying

arXiv:2605.07985v1 Announce Type: cross Abstract: Selecting the optimal LLM inference configuration requires evaluation across hardware, serving engines, attention backends, and model architectures, s

arXiv:2605.07289v1 Announce Type: cross Abstract: ReDoS is a well-known type of algorithmic complexity attack, where an adversary supplies maliciously crafted strings to a regular expression matching

arXiv:2605.02741v1 Announce Type: cross Abstract: The promise of Large Language Models in automated software engineering is often measured by functional correctness, overlooking the critical issue of

arXiv:2605.00073v1 Announce Type: new Abstract: Decentralized, agentic AI marketplaces are rapidly emerging to support software engineering tasks such as debugging, patch generation, and security audi

arXiv:2605.00907v1 Announce Type: new Abstract: Large language models (LLMs) and multimodal large models (MLLMs) are increasingly used for transportation tasks such as regulation question answering, t

arXiv:2604.26955v1 Announce Type: cross Abstract: AI tutoring systems in engineering labs face a tension between providing sufficient assistance and preserving learning opportunities. Existing systems