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arXiv:2602.15539v1 Announce Type: new Abstract: Recent studies have explored the combination of multiple LoRAs to simultaneously generate user-specified subjects and styles. However, most existing approaches...
arXiv:2602.15540v1 Announce Type: new Abstract: This paper introduces Perspectives, an interactive extension of the Discourse Analysis Tool Suite designed to empower Digital Humanities (DH) scholars...
arXiv:2602.15543v1 Announce Type: new Abstract: In robotics, Vision-Language-Action (VLA) models that integrate diverse multimodal signals from multi-view inputs have emerged as an effective approach. However,...
arXiv:2602.15546v1 Announce Type: new Abstract: The ability to accurately perform counterfactual inference on time series is crucial for decision-making in fields like finance, healthcare, and...
arXiv:2602.15547v1 Announce Type: new Abstract: Text embedding models are widely used for semantic similarity tasks, including information retrieval, clustering, and classification. General-purpose models are typically...
arXiv:2602.15549v1 Announce Type: new Abstract: Vision-language model (VLM) shows promise for high-level planning in smart manufacturing, yet their deployment in dynamic workcells faces two critical...
arXiv:2602.15552v1 Announce Type: new Abstract: This study investigates the impact of regularization of latent spaces through truncation on the quality of generated test inputs for...
arXiv:2602.15553v1 Announce Type: new Abstract: The Personal AI landscape is currently dominated by "Black Box" Retrieval-Augmented Generation. While standard vector databases offer statistical matching, they...
arXiv:2602.15554v1 Announce Type: new Abstract: Urban infrastructure degrades over time, necessitating periodic renovation to maintain functionality and safety. When renovation is delayed beyond the infrastructure's...
arXiv:2602.15556v1 Announce Type: new Abstract: LVLMs have achieved strong multimodal reasoning capabilities but remain prone to hallucinations, producing outputs inconsistent with visual inputs or user...
arXiv:2602.15563v1 Announce Type: new Abstract: Quantization-aware training (QAT) is an effective method to drastically reduce the memory footprint of LLMs while keeping performance degradation at...
arXiv:2602.15564v1 Announce Type: new Abstract: Text-to-SQL has recently achieved impressive progress, yet remains difficult to apply effectively in real-world scenarios. This gap stems from the...
arXiv:2602.15566v1 Announce Type: new Abstract: We study the fair allocation of indivisible goods among agents with additive valuations. The fair division literature has traditionally focused...
arXiv:2602.15567v1 Announce Type: new Abstract: Robot motion distributions often exhibit multi-modality and require flexible generative models for accurate representation. Streaming Flow Policies (SFPs) have recently...
arXiv:2602.15569v1 Announce Type: new Abstract: Agentic AI assistants that autonomously perform multi-step tasks raise open questions for user experience: how should such systems communicate progress...
arXiv:2602.15571v1 Announce Type: new Abstract: Predictive coding (PC) is a biologically inspired algorithm for training neural networks that relies only on local updates, allowing parallel...
arXiv:2602.15572v1 Announce Type: new Abstract: Agent-based modelling (ABM) is a widespread approach to simulate complex systems. Advancements in computational processing and storage have facilitated the...
arXiv:2602.15578v1 Announce Type: new Abstract: Depression manifests through a diverse set of symptoms such as sleep disturbance, loss of interest, and concentration difficulties. However, most...
arXiv:2602.15579v1 Announce Type: new Abstract: Intracoronary Optical Coherence Tomography (OCT) enables high-resolution visualization of coronary vessel anatomy but presents challenges due to noise, imaging artifacts,...
arXiv:2602.15580v1 Announce Type: new Abstract: When a multimodal Transformer answers a visual question, is the prediction driven by visual evidence, linguistic reasoning, or genuinely fused...
arXiv:2602.15584v1 Announce Type: new Abstract: Aligning functional schematics with 2D and 3D scene acquisitions is crucial for building digital twins, especially for old industrial facilities...
arXiv:2602.15586v1 Announce Type: new Abstract: This paper provides statistical guarantees on the accuracy of dynamical models learned from dependent data sequences. Specifically, we develop uniform...
arXiv:2602.15591v1 Announce Type: new Abstract: Testing functionality in Software-Defined Vehicles is challenging because requirements are written in natural language, specifications combine text, tables, and diagrams,...
arXiv:2602.15593v1 Announce Type: new Abstract: Recurrent and deep neural networks (RNNs/DNNs) are cornerstone architectures in machine learning. Remarkably, RNNs differ from DNNs only by weight...