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arXiv:2601.20650v1 Announce Type: new Abstract: Long-horizon, repetitive workflows are common in professional settings, such as processing expense reports from receipts and entering student grades from...
arXiv:2601.20653v1 Announce Type: new Abstract: We study the Multiserver-Job Queuing Model (MJQM) with general independent arrivals and service times under FCFS scheduling, using stochastic recurrence...
arXiv:2601.20655v1 Announce Type: new Abstract: The rapid growth of AI-generated content (AIGC) has enabled high-quality creative production across diverse domains, yet existing systems face critical...
arXiv:2601.20656v1 Announce Type: new Abstract: Face morphing attacks present a significant threat to face recognition systems used in electronic identity enrolment and border control, particularly...
arXiv:2601.20659v1 Announce Type: new Abstract: Assessing ways in which Language Models can reduce their hallucinations and improve the outputs' quality is crucial to ensure their...
arXiv:2601.20661v1 Announce Type: new Abstract: Skill assessment in procedural videos is crucial for the objective evaluation of human performance in settings such as manufacturing and...
arXiv:2601.20662v1 Announce Type: new Abstract: Ensuring the integrity of software build artifacts is an increasingly important concern for modern software engineering, driven by increasingly sophisticated...
arXiv:2601.20663v1 Announce Type: new Abstract: Accurate neuronavigation is essential for generating the intended effect with transcranial magnetic stimulation (TMS). Precise coil placement also directly influences...
arXiv:2601.20664v1 Announce Type: new Abstract: Entity Resolution (ER) is a critical task for data integration, yet state-of-the-art supervised deep learning models remain impractical for many...
arXiv:2601.20666v1 Announce Type: new Abstract: We introduce a novel framework for learning context-aware runtime monitors for AI-based control ensembles. Machine-learning (ML) controllers are increasingly deployed...
arXiv:2601.20668v1 Announce Type: new Abstract: Training reinforcement learning (RL) policies for legged robots remains challenging due to high-dimensional continuous actions, hardware constraints, and limited exploration....
arXiv:2601.20671v1 Announce Type: new Abstract: Tip-of-the-tongue (ToT) known-item retrieval involves re-finding an item for which the searcher does not reliably recall an identifier. ToT information...
arXiv:2601.20674v1 Announce Type: new Abstract: This study applies Large Language Models (LLMs) to two foundational Electronic Health Record (EHR) data science tasks: structured data querying...
arXiv:2601.20675v1 Announce Type: new Abstract: Prompt learning (PL) has emerged as an effective strategy to adapt vision-language models (VLMs), such as CLIP, for downstream tasks...
arXiv:2601.20676v1 Announce Type: new Abstract: Visual Question-Answering (VQA) is a challenging multimodal task that requires integrating visual and textual information to generate accurate responses. While...
arXiv:2601.20677v1 Announce Type: new Abstract: We present the first rigorous convergence analysis of the smoothed adaptive finite element method (S-AFEM) proposed in [Mulita, Giani, Heltai:...
arXiv:2601.20678v1 Announce Type: new Abstract: Consider the Gaussian wiretap channel, where a transmitter wishes to send a confidential message to a legitimate receiver in the...
arXiv:2601.20679v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable progress in code generation, yet their potential for software protection remains largely untapped....
arXiv:2601.20680v1 Announce Type: new Abstract: Automated narrative intelligence systems for social media monitoring face significant scalability challenges when processing continuous data streams using traditional batch...
arXiv:2601.20682v1 Announce Type: new Abstract: Tendon-driven anthropomorphic robotic hands often lack direct joint angle sensing, as the integration of joint encoders can compromise mechanical compactness...
arXiv:2601.20683v1 Announce Type: new Abstract: As conversational agents become increasingly common in behaviour change interventions, understanding optimal feedback delivery mechanisms becomes increasingly important. However, choosing...
arXiv:2601.20686v1 Announce Type: new Abstract: Change Point Detection (CPD) is a critical task in time series analysis, aiming to identify moments when the underlying data-generating...
arXiv:2601.20687v1 Announce Type: new Abstract: Due to constraints on privacy, cost, and latency, on-premise deployment of small models is increasingly common. However, most practical pipelines...
arXiv:2601.20689v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) have demonstrated strong capabilities in image quality assessment (IQA) tasks. However, adapting such large-scale...