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arXiv:2603.03526v1 Announce Type: new Abstract: Western governments have adopted an assortment of counter-hybrid threat measures to defend against hostile actions below the conventional military threshold....
arXiv:2603.03527v1 Announce Type: new Abstract: Vision-Language Models (VLMs) with their multimodal capabilities have demonstrated remarkable success in almost all domains, including education, transportation, healthcare, energy,...
arXiv:2603.03529v1 Announce Type: new Abstract: We introduce mlx-snn, the first spiking neural network (SNN) library built natively on Apple's MLX framework. As SNN research grows...
arXiv:2603.03530v1 Announce Type: new Abstract: Frozen self-supervised representations often transfer well with only a few labels across many semantic tasks. We argue that a single...
arXiv:2603.03531v1 Announce Type: new Abstract: Accurate prediction of terrestrial ecosystem carbon fluxes (e.g., CO$_2$, GPP, and CH$_4$) is essential for understanding the global carbon cycle...
arXiv:2603.03532v1 Announce Type: new Abstract: Voting Advice Applications (VAA) are tools designed to help voters compare political candidates on policy preferences prior to elections. VAAs...
arXiv:2603.03535v1 Announce Type: new Abstract: While large language models (LLMs) fine-tuned with lightweight adapters achieve strong performance across diverse tasks, their performance on individual tasks...
arXiv:2603.03536v1 Announce Type: new Abstract: Current LLM-based conversational recommender systems (CRS) primarily optimize recommendation accuracy and user satisfaction. We identify an underexplored vulnerability in which...
arXiv:2603.03537v1 Announce Type: new Abstract: Rapid acceleration and burst maneuvers in underwater robots depend less on maintaining precise resonance and more on force--velocity phase alignment...
arXiv:2603.03538v1 Announce Type: new Abstract: Large language models with chain-of-thought generation have demonstrated great potential for producing complex mathematical proofs. However, their reasoning can often...
arXiv:2603.03541v1 Announce Type: new Abstract: Automated question-answering (QA) systems increasingly rely on retrieval-augmented generation (RAG) to ground large language models (LLMs) in authoritative medical knowledge,...
arXiv:2603.03543v1 Announce Type: new Abstract: We present Tucano 2, a fully open suite of large language models (LLMs) with 0.5-3.7 billion parameters, designed to address...
arXiv:2603.03544v1 Announce Type: new Abstract: While multi-modal Visual Language Models (VLMs) have demonstrated significant success across various domains, the integration of VLMs into recommendation and...
arXiv:2603.03546v1 Announce Type: new Abstract: Accurate positioning, navigation, and timing (PNT) is fundamental to the operation of modern technologies and a key enabler of autonomous...
arXiv:2603.03555v1 Announce Type: new Abstract: MoltBook is a large-scale multi-agent coordination environment where over 770,000 autonomous LLM agents interact without human participation, offering the first...
arXiv:2603.03556v1 Announce Type: new Abstract: Reliable positioning in dense urban environments remains challenging due to frequent GNSS signal blockage, multipath, and rapidly varying satellite geometry....
arXiv:2603.03560v1 Announce Type: new Abstract: Many smart grid frameworks, such as demand response programs, require accurate information about consumers' parameters (e.g., flexibility) at the aggregator...
arXiv:2603.03564v1 Announce Type: new Abstract: Recent advances in large vision models (LVMs) have shifted from modality-specific designs toward unified architectures that jointly process images, videos,...
arXiv:2603.03565v1 Announce Type: new Abstract: Conversational shopping assistants (CSAs) represent a compelling application of agentic AI, but moving from prototype to production reveals two underexplored...
arXiv:2603.03566v1 Announce Type: new Abstract: This paper studies the relationship between human eye gaze time on words in source code and the Semantic Neighborhood Density...
arXiv:2603.03571v1 Announce Type: new Abstract: Purpose: Monocular depth estimation (MDE) is vital for scene understanding in minimally invasive surgery (MIS). However, endoscopic video sequences are...
arXiv:2603.03573v1 Announce Type: new Abstract: Discrete biological sequence optimization requires iterative refinement under strict syntactic constraints. Diffusion models offer progressive refinement but do not naturally...
arXiv:2603.03574v1 Announce Type: new Abstract: This paper presents a scenario generation framework that creates diverse, parametrized, and safety-critical driving situations to validate the safety features...
arXiv:2603.03577v1 Announce Type: new Abstract: Detecting and segmenting novel object instances in open-world environments is a fundamental problem in robotic perception. Given only a small...