Search: “automated”

arXiv:2606.13670v2 Announce Type: replace Abstract: Reproducibility in the social and behavioral sciences is typically evaluated by independent researchers who reanalyze the original data to assess wh

arXiv:2606.27287v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to screen and rank job applicants, creating incentives for candidates to strategically manipulate alg

arXiv:2606.25487v1 Announce Type: new Abstract: Almost every paper on LLM jailbreaks and prompt injection reports an attack-success rate (ASR), and that number is assigned not by people but by an auto

arXiv:2606.24965v1 Announce Type: cross Abstract: Reasoning about relational structures remains a significant challenge for neural models, particularly when they must systematically apply learned know

arXiv:2606.13535v3 Announce Type: replace-cross Abstract: Particle physics collider experiments provide Rivet routines as part of the analysis preservation strategy for model-independent measurements.

Talos was built to help resolve a major bottleneck in genomic medicine: human review time. The open-source system recovered 90% of in-scope diagnoses while surfacing just 1.3 candidate variants per pa

arXiv:2606.23689v1 Announce Type: cross Abstract: Learning robust dexterous grasping requires real-world data that records the physical outcomes of grasp attempts. Such data is hard to obtain at scale

Artificial intelligence-native loan origination startup Lama AI Inc. said today it has closed on a 10 million capital infusion, bringing its total amount raised to date to more than 20 million after g

arXiv:2510.08622v2 Announce Type: replace Abstract: Software requirements are derived from a variety of elicitation techniques, many of which have a conversational nature, like interviews. However, ev

arXiv:2606.09830v1 Announce Type: new Abstract: In modern educational systems, Automatic Text Scoring (ATS) plays a central role by enabling scalable and consistent evaluation of learner responses wit

arXiv:2606.10394v1 Announce Type: new Abstract: Large language models are increasingly used to power personal agents for everyday applications, but evaluating these agents remains a challenge. Existin

arXiv:2606.08270v1 Announce Type: cross Abstract: University Academic Management Information Systems (ACMIS) are high-value targets for a wide spectrum of security threats including brute-force login

arXiv:2604.01039v2 Announce Type: replace-cross Abstract: System Instructions in Large Language Models (LLMs) are commonly used to enforce safety policies, define agent behavior, and protect sensitive

arXiv:2606.08800v1 Announce Type: new Abstract: In high-stakes settings such as brand compliance, clinical care, and content moderation, machine learning cannot be deployed as opaque oracles: practiti

arXiv:2606.08855v1 Announce Type: new Abstract: This paper examines the limitations of fully digital and partially digital e-assessment approaches in summative examinations in higher education. The an

arXiv:2601.20408v2 Announce Type: replace-cross Abstract: Enterprise LLM deployment faces a critical scalability challenge: organizations must optimize models systematically to scale AI initiatives wi

arXiv:2512.15552v2 Announce Type: replace Abstract: A General Service List (GSL) is a commonly used resource for language learners to identify important English words. Traditional GSL creation is reso

arXiv:2606.04594v1 Announce Type: cross Abstract: LLM serving frameworks are quickly evolving with a complex software stack and a vast number of optimizations. The rapid development process can introd

arXiv:2606.02809v1 Announce Type: new Abstract: Evaluating vision-language models (VLMs) on medical images requires benchmarks that are clinically grounded, scalable, and controlled for evaluation con

arXiv:2602.20213v2 Announce Type: replace-cross Abstract: The evaluation of Large Language Models (LLMs) for code generation relies heavily on the quality and robustness of test cases. However, existi

arXiv:2606.01825v1 Announce Type: new Abstract: Text-Based Person Search (TBPS) aims to retrieve pedestrian images using natural language queries. However, existing TBPS models, especially those based

arXiv:2606.02540v1 Announce Type: new Abstract: Agent skills occupy a privileged position in the agent workflow, as agents are expected to implicitly follow and execute them, rendering third-party ski

arXiv:2605.31264v1 Announce Type: new Abstract: LLM agents are increasingly expected not only to complete isolated tasks, but also to carry bounded representations of human expertise, judgment, and in

arXiv:2509.23694v5 Announce Type: replace Abstract: Search agents connect LLMs to the Internet, enabling them to access broader and more up-to-date information. However, this also introduces a new thr

arXiv:2410.00995v3 Announce Type: replace Abstract: The automatic synthesis of analog circuits presents significant challenges. Most existing approaches formulate the problem as a single-objective opt

arXiv:2605.26978v1 Announce Type: new Abstract: Text-to-speech (TTS) evaluation for low-resource non-Latin-script languages can fail when it relies on a single ASR round-trip word error rate (WER). A

arXiv:2605.26079v1 Announce Type: new Abstract: Modern AI benchmarks operate at a complexity that outpaces traditional verification methods. Tasks authored by domain experts often contain implicit ass

arXiv:2310.01285v2 Announce Type: replace-cross Abstract: Recent work has proposed Wasserstein k-means (Wk-means) clustering as a powerful method to classify regimes in time series data, and one-dimen

arXiv:2605.23917v1 Announce Type: new Abstract: Modern scientific discovery is bottlenecked not by data scarcity, but by the inability to synthesize fragmented knowledge into actionable hypotheses. Th

arXiv:2503.11657v3 Announce Type: replace Abstract: Large language models have demonstrated remarkable capabilities in natural language processing tasks requiring multi-step logical reasoning capabili

arXiv:2605.23454v1 Announce Type: new Abstract: Rubric-based rewards offer a promising way to extend reinforcement learning (RL) for large language models beyond tasks with automatically verifiable an

arXiv:2605.23473v1 Announce Type: cross Abstract: Bayesian optimization is widely employed for optimizing complex black-box functions but struggles with the curse of dimensionality. Random embedding,

Simon Willison discusses whether coding agents should automatically generate tests alongside the code they produce, addressing a key quality assurance consideration in AI-assisted development. This li

arXiv:2605.22722v1 Announce Type: new Abstract: Autonomous parking requires efficient path planning that ensures kinematic feasibility and collision avoidance in constrained environments. Hybrid A* is

arXiv:2605.21154v1 Announce Type: new Abstract: Mental health has become a global priority, leading to a massive administrative burden in the coding of clinical diagnoses. This study proposes the auto

arXiv:2605.20249v1 Announce Type: new Abstract: Gaussian Process (GP) kernels are central to Bayesian optimization (BO), yet designing effective kernels for high-dimensional problems still relies on e

arXiv:2605.21076v1 Announce Type: new Abstract: Grading German legal exam solutions faces growing volumes and a shortage of qualified graders, delaying feedback and creating a bottleneck. At the same

arXiv:2605.19646v1 Announce Type: cross Abstract: Advancements in clinical Brain-Computer Interfaces (BCIs) depend on precise and reliable signal interpretation. However, the high-dimensional and nois

arXiv:2510.20584v3 Announce Type: replace-cross Abstract: Assessing communication and collaboration at scale depends on a labor-intensive task of coding communication data into categories according to

arXiv:2502.18632v4 Announce Type: replace Abstract: Knowledge components (KCs) mapped to problems help model student learning, tracking their mastery levels on fine-grained skills thereby facilitating

arXiv:2605.16894v1 Announce Type: new Abstract: Reinforcement Learning (RL) uses rewards to guide learning, yet reward design is typically hand-crafted using heuristics that can be difficult to tune.

arXiv:2605.16377v1 Announce Type: cross Abstract: Transparent and standardized reporting is essential for reproducible scientific research, yet adherence to reporting guidelines remains inconsistent b

arXiv:2508.02332v3 Announce Type: replace Abstract: The performance of Bayesian optimization (BO), a highly sample-efficient method for expensive black-box problems, is critically governed by the sele

arXiv:2602.17949v2 Announce Type: replace-cross Abstract: Background: Clinical named entity recognition tools commonly map free text to Unified Medical Language System (UMLS) Concept Unique Identifier

arXiv:2601.15161v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly used for clinical decision support, where hallucinations and unsafe suggestions may pose direct

arXiv:2605.12022v1 Announce Type: new Abstract: Large Language Models (LLMs) achieve strong performance on standard knowledge evaluation benchmarks, yet recent work shows that their knowledge capabili