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arXiv:2603.04933v1 Announce Type: new Abstract: In this paper, we present AILS-NTUA system for Track-A of SemEval-2026 Task 3 on Dimensional Aspect-Based Sentiment Analysis (DimABSA), which...
arXiv:2603.04936v1 Announce Type: new Abstract: Vehicular edge intelligence (VEI) is vital for future intelligent transportation systems. However, traditional centralized learning in dynamic vehicular networks faces...
arXiv:2603.04937v1 Announce Type: new Abstract: Despite many advances in query optimization, indexing techniques, and data storage, modern data platforms still face difficulties in delivering robust...
arXiv:2603.04938v1 Announce Type: new Abstract: This paper investigates person detection and tracking in an industrial indoor workspace using a LiDAR mounted on an overhead crane....
arXiv:2603.04943v1 Announce Type: new Abstract: Target speaker extraction (TSE) aims to isolate a specific speaker's voice from multi-speaker mixtures. Despite strong benchmark results, real-world performance...
arXiv:2603.04944v1 Announce Type: new Abstract: Modern vehicles increasingly rely on advanced driver-assistance systems (ADAS), with radars playing a key role due to their cost-effectiveness and...
arXiv:2603.04945v1 Announce Type: new Abstract: Training automatic speech recognition (ASR) models increasingly relies on decentralized federated learning to ensure data privacy and accessibility, producing multiple...
arXiv:2603.04947v1 Announce Type: new Abstract: Prostate cancer being one of the frequently diagnosed malignancy in men, the rising demand for biopsies places a severe workload...
arXiv:2603.04948v1 Announce Type: new Abstract: Scaling inference-time compute for Large Language Models (LLMs) has unlocked unprecedented reasoning capabilities. However, existing inference-time scaling methods typically rely...
arXiv:2603.04949v1 Announce Type: new Abstract: The improvement of web agents on current benchmarks raises the question: Do today's agents perform just as well when the...
arXiv:2603.04950v1 Announce Type: new Abstract: Unlike conventional single-image models, differential medical VQA frameworks process multiple images to identify differences, mirroring the comparative diagnostic workflow of...
arXiv:2603.04951v1 Announce Type: new Abstract: While RAG has greatly enhanced LLMs, extending this paradigm to Time-Series Foundation Models (TSFMs) remains a challenge. This is exemplified...
arXiv:2603.04952v1 Announce Type: new Abstract: This document details the Fully Homomorphic Modified Rivest Scheme (FHMRS), a security issue in FHMRS, and a modification to FHMRS...
arXiv:2603.04955v1 Announce Type: new Abstract: In this work, we investigate uncertainty-aware neural network models for blood glucose prediction and adverse glycemic event identification in Type...
arXiv:2603.04956v1 Announce Type: new Abstract: This paper considers the problem of converting a given dense linear layer to low precision. The tradeoff between compressed length...
arXiv:2603.04957v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have achieved strong performance in vision-language understanding, yet many existing approaches rely on large-scale architectures and...
arXiv:2603.04958v1 Announce Type: new Abstract: We introduce a novel camera model for monocular 3D Morphable Model (3DMM) regression methods that effectively captures the perspective distortion...
arXiv:2603.04959v1 Announce Type: new Abstract: The importance of replication is often discussed and advocated -- not only in the domains of visualization and HCI, but...
arXiv:2603.04962v1 Announce Type: new Abstract: As the penetration level of distributed energy resources (DERs) continues to rise, traditional frequency and voltage support from synchronous machines...
arXiv:2603.04964v1 Announce Type: new Abstract: To obtain a language model for a target domain (e.g. math), the current paradigm is to pre-train on a vast...
arXiv:2603.04966v1 Announce Type: new Abstract: The escalating energy demands of artificial intelligence pose a critical challenge to conventional computing. Leveraging the efficiency of event-driven, in-memory...
arXiv:2603.04968v1 Announce Type: new Abstract: Preference alignment is an essential step in adapting large language models (LLMs) to human values, but existing approaches typically depend...
arXiv:2603.04969v1 Announce Type: new Abstract: Multi-party conversation generation, such as smart reply and collaborative assistants, is an increasingly important capability of generative AI, yet its...
arXiv:2603.04971v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) decouples model capacity from per-token computation, yet their scalability remains limited by the physical dimensions of depth and...