arXiv:2501.05675v5 Announce Type: replace Abstract: In anomaly detection, methods based on large language models (LLMs) can incorporate expert knowledge by reading professional document, while task-specific small models excel at extracting normal data patterns and detecting value fluctuations from training data of target applications. Inspired by the human nervous system, where the brain stores expert knowledge […]
UMI-Underwater: Learning Underwater Manipulation without Underwater Teleoperation
arXiv:2603.27012v1 Announce Type: cross Abstract: Underwater robotic grasping is difficult due to degraded, highly variable imagery and the expense of collecting diverse underwater demonstrations. We introduce a system that (i) autonomously collects successful underwater grasp demonstrations via a self-supervised data collection pipeline and (ii) transfers grasp knowledge from on-land human demonstrations through a depth-based affordance […]
TokenDance: Token-to-Token Music-to-Dance Generation with Bidirectional Mamba
arXiv:2603.27314v1 Announce Type: new Abstract: Music-to-dance generation has broad applications in virtual reality, dance education, and digital character animation. However, the limited coverage of existing 3D dance datasets confines current models to a narrow subset of music styles and choreographic patterns, resulting in poor generalization to real-world music. Consequently, generated dances often become overly simplistic […]
Multi-Level Barriers to Generative AI Adoption Across Disciplines and Professional Roles in Higher Education
arXiv:2603.27052v1 Announce Type: cross Abstract: Generative Artificial Intelligence (GenAI) is rapidly reshaping higher education, yet barriers to its adoption across different disciplines and institutional roles remain underexplored. Existing literature frequently attributes adoption barriers to individual-level factors such as perceived usefulness and ease of use. This study instead investigates whether such barriers are structurally produced. Drawing […]
FlipVQA: Scaling Multi-modal Instruction Tuning via Textbook-to-Knowledge Synthesis
arXiv:2511.16216v2 Announce Type: replace Abstract: Textbooks are among the richest repositories of human-verified reasoning knowledge, yet their complex layouts contain multi-column typesetting, cross-page question answer separation, and interleaved figures, make automated extraction of structured QA and VQA pairs extremely challenging. Existing alternatives either synthesize data from scratch, which lacks authentic problem contexts, or rely on […]
Dynamic resource matching in manufacturing using deep reinforcement learning
arXiv:2603.27066v1 Announce Type: cross Abstract: Matching plays an important role in the logical allocation of resources across a wide range of industries. The benefits of matching have been increasingly recognized in manufacturing industries. In particular, capacity sharing has received much attention recently. In this paper, we consider the problem of dynamically matching demand-capacity types of […]
CounterMoral: Editing Morals in Language Models
arXiv:2603.27338v1 Announce Type: new Abstract: Recent advancements in language model technology have significantly enhanced the ability to edit factual information. Yet, the modification of moral judgments, a crucial aspect of aligning models with human values, has garnered less attention. In this work, we introduce CounterMoral, a benchmark dataset crafted to assess how well current model […]
RDEx-MOP: Indicator-Guided Reconstructed Differential Evolution for Fixed-Budget Multiobjective Optimization
arXiv:2603.27092v1 Announce Type: cross Abstract: Multiobjective optimisation in the CEC 2025 MOP track is evaluated not only by final IGD values but also by how quickly an algorithm reaches the target region under a fixed evaluation budget. This report documents RDEx-MOP, the reconstructed differential evolution variant used in the IEEE CEC 2025 numerical optimisation competition […]
Modelling SARS-CoV-2 epidemics via compartmental and cellular automaton SEIRS model with temporal immunity and vaccination
arXiv:2603.22498v2 Announce Type: replace Abstract: We consider the SEIRS epidemiology model with such features of the COVID-19 outbreak as: abundance of unidentified infected individuals, limited time of immunity and a possibility of vaccination. The control of the pandemic dynamics is possible by restricting the transmission rate, increasing identification and isolation rate of infected individuals, and […]
Bayes-MICE: A Bayesian Approach to Multiple Imputation for Time Series Data
arXiv:2603.27142v1 Announce Type: cross Abstract: Time-series analysis is often affected by missing data, a common problem across several fields, including healthcare and environmental monitoring. Multiple Imputation by Chained Equations (MICE) has been prominent for imputing missing values through “fully conditional specification”. We extend MICE using the Bayesian framework (Bayes-MICE), utilising Bayesian inference to impute missing […]
A Comparative Study in Surgical AI: Datasets, Foundation Models, and Barriers to Med-AGI
arXiv:2603.27341v1 Announce Type: new Abstract: Recent Artificial Intelligence (AI) models have matched or exceeded human experts in several benchmarks of biomedical task performance, but have lagged behind on surgical image-analysis benchmarks. Since surgery requires integrating disparate tasks — including multimodal data integration, human interaction, and physical effects — generally-capable AI models could be particularly attractive […]
An End-to-end Flight Control Network for High-speed UAV Obstacle Avoidance based on Event-Depth Fusion
arXiv:2603.27181v1 Announce Type: cross Abstract: Achieving safe, high-speed autonomous flight in complex environments with static, dynamic, or mixed obstacles remains challenging, as a single perception modality is incomplete. Depth cameras are effective for static objects but suffer from motion blur at high speeds. Conversely, event cameras excel at capturing rapid motion but struggle to perceive […]