Search: “automated”

arXiv:2610.02369v1 Announce Type: cross Abstract: Human-computer interaction (HCI) is in the middle of a transition: large language models can now generate functional user interfaces (UIs) on demand f

arXiv:2609.37454v1 Announce Type: new Abstract: Underwriters in commercial Property and Casualty (P&C) insurance spend 30 to 40% of their time on administrative work rather than risk judgment, and a s

arXiv:2506.02914v3 Announce Type: replace Abstract: The contemporary paradigm of scaling data annotation, crucial for developing machine learning solutions, is to hire ordinary human annotators and in

arXiv:2609.30298v1 Announce Type: new Abstract: Systematic reviews (SR) are essential for evidence-based research, but their screening phase is highly time-consuming and labor-intensive. Large languag

arXiv:2609.27257v1 Announce Type: new Abstract: Enterprise data agents must preserve organization specific semantics, not just translate questions into queries. We present ChinaUnicom DataAgent (UniDa

arXiv:2609.24586v1 Announce Type: new Abstract: Traditional evaluation metrics provides numerical values but often lack comprehensibility, hindering effective differentiation of model performances. Ou

arXiv:2609.20886v1 Announce Type: cross Abstract: Business intelligence (BI) is a cornerstone of enterprise decision-making and is widely used by enterprise users in software such as Power BI and Tabl

arXiv:2609.10629v1 Announce Type: new Abstract: Quadratic Unconstrained Binary Optimization (QUBO) is a central formulation for combinatorial optimization and has gained increasing attention due to it

arXiv:2609.07165v1 Announce Type: new Abstract: Learning-by-Demonstration (LbD) enables intuitive robot programming by capturing expert skills, which is crucial for agility in high-mix, low- volume ma

arXiv:2609.04871v1 Announce Type: new Abstract: Improving an industrial recommender is an iterative research-and-engineering process rather than a direct path from idea to deployment. In extbf{DASHEN,

arXiv:2609.03553v1 Announce Type: new Abstract: Policy analysis requires more than predicting whether a proposal will pass: it requires identifying who will be affected, how those actors respond, and

arXiv:2608.29408v1 Announce Type: new Abstract: This study introduces a Visual Question Answering model designed specifically for nondestructive evaluation applications. VQA models allow inspectors to

arXiv:2608.24103v1 Announce Type: new Abstract: Commercial design platforms increasingly edit documents through large language model (LLM) agents, but two practical problems block reliable deployment:

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

arXiv:2608.16541v1 Announce Type: cross Abstract: Objective assessment of learning remains a fundamental challenge in education. Electroencephalography (EEG) provides a direct, non-invasive window int

arXiv:2608.00198v1 Announce Type: new Abstract: Environmental time-series causal discovery requires expert decisions about method choice, conditional-independence tests, lag horizons, sample-size adeq

arXiv:2607.29422v1 Announce Type: cross Abstract: Automated vulnerability repair aims to reduce the time and effort required to patch security flaws from a vulnerability triage report. Recent agentic

arXiv:2604.05150v2 Announce Type: replace-cross Abstract: We study compiled AI, a paradigm in which large language models generate executable code artifacts during a compilation phase, after which wor

arXiv:2607.05915v1 Announce Type: new Abstract: PCB routing is the task of connecting the nets of a board with copper traces under strict design rules, yet learning-based methods still lag behind rule

arXiv:2406.07089v4 Announce Type: replace Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have shown promise for remote sensing tasks such as visual question answering and scene

arXiv:2602.18767v3 Announce Type: replace-cross Abstract: In Machine-Assisted Theorem Proving, a theorem proving agent searches for a sequence of expressions and tactics that can prove a statement in

arXiv:2606.30801v1 Announce Type: new Abstract: Personalization algorithms determine what content users encounter on online platforms. Auditing these systems is difficult because independent auditors

arXiv:2606.28277v1 Announce Type: cross Abstract: Artificial intelligence is driving a revolution in scientific discovery, accelerating everything from hypothesis generation to mathematical theorem pr

arXiv:2606.27180v1 Announce Type: cross Abstract: Sparse rewards are inherently challenging for reinforcement learning agents as they lack intermediate feedback to guide exploration and to correctly a

arXiv:2606.11166v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly described as performing at the level of human experts on knowledge economy tasks. These claims are prima

arXiv:2603.20253v2 Announce Type: replace-cross Abstract: Evaluating LLM agents for scientific tasks has focused on token costs while ignoring tool-use costs like simulation time and experimental reso

arXiv:2502.08047v5 Announce Type: replace Abstract: Recent progress in GUI agents has substantially improved visual grounding, yet robust planning remains challenging, particularly when the environmen

arXiv:2605.22608v1 Announce Type: new Abstract: Agentic systems are becoming more capable: agents define strategies, take actions, and interact with different environments. This autonomy poses serious

arXiv:2605.12835v1 Announce Type: new Abstract: Large language models can extract local causal claims from text, but those claims become more useful when organized as persistent, navigable world model

arXiv:2605.08291v1 Announce Type: cross Abstract: EDA problems are graph-structured, but not all graph-structured problems call for the same GNN computation. We argue that successful GNN-for-EDA metho

arXiv:2605.03231v1 Announce Type: new Abstract: What if a browser agent could learn your work simply by watching you do it? We present cotomi Act, a browser-based computer-using agent that combines re

arXiv:2603.25169v2 Announce Type: replace Abstract: LLM performance is highly sensitive to prompt design, yet whether automatic prompt optimization can replace expert prompt engineering in linguistic

arXiv:2604.25292v1 Announce Type: new Abstract: This paper addresses the problem of traffic congestion management in fixed-wing unmanned aerial vehicle (UAV) corridors by further developing a recently

arXiv:2604.23430v1 Announce Type: cross Abstract: The relentless expansion of scientific literature presents significant challenges for navigation and knowledge discovery. Within Research Information

arXiv:2604.21375v1 Announce Type: cross Abstract: Autonomous GUI agents face two fundamental challenges: early stopping, where agents prematurely declare success without verifiable evidence, and repet

arXiv:2508.21675v3 Announce Type: replace Abstract: Misleading visualizations are a potent driver of misinformation on social media and the web. By violating chart design principles, they distort data

arXiv:2512.03053v2 Announce Type: replace-cross Abstract: We show for invertible problems that transform data from a source domain (for example, Logic Condition Tables (LCTs)) to a destination domain

arXiv:2604.14616v1 Announce Type: new Abstract: Clinical value set authoring -- the task of identifying all codes in a standardized vocabulary that define a clinical concept -- is a recurring bottlene

arXiv:2604.13822v1 Announce Type: new Abstract: MLLM-based GUI agents have demonstrated strong capabilities in complex user interface interaction tasks. However, long-horizon scenarios remain challeng

arXiv:2508.06445v3 Announce Type: replace-cross Abstract: The rapid rise of Generative AI (GenAI), particularly LLMs, poses concerns for journalistic integrity and authorship. This study examines AI-g

arXiv:2604.09155v1 Announce Type: cross Abstract: Graphical user interface (GUI) agents powered by vision language models (VLMs) are rapidly moving from passive assistance to autonomous operation. How

arXiv:2610.04878v1 Announce Type: cross Abstract: Human-agent evaluations often compress interaction into a single performance score, even when human and automated policies adapt differently over time

arXiv:2604.17341v1 Announce Type: new Abstract: Diabetic retinopathy (DR) is a leading cause of vision impairment worldwide, and automated grading systems play a crucial role in large-scale screening

arXiv:2608.17501v1 Announce Type: new Abstract: Recent efforts toward fully automated AI scientists have demonstrated that language-model agents can generate hypotheses, execute experiments, and draft

arXiv:2608.04704v1 Announce Type: new Abstract: Reliable environment monitoring is essential for the safe and efficient operation of automated railway systems, covering all Grades of Automation (GoA),

arXiv:2610.20563v1 Announce Type: cross Abstract: Automated research with LLM agents has shown promising results in various domains. Through iterative refinement and scored verifiers, LLM agents are c