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arXiv:2601.17152v1 Announce Type: new Abstract: Multi-agent large language model (LLM) and vision-language model (VLM) debate systems employ specialized roles for complex problem-solving, yet model specializations...
arXiv:2601.17155v1 Announce Type: new Abstract: This paper investigates the application of zonotope-based reachability analysis to low-thrust spacecraft in both two-body and cislunar environments. Reachable sets...
arXiv:2601.17156v1 Announce Type: new Abstract: Intent detection, a fundamental text classification task, aims to identify and label the semantics of user queries, playing a vital...
arXiv:2601.17158v1 Announce Type: new Abstract: The search for extraterrestrial life has long been a primary focus of scientific exploration, driven by rapid advancements in technology...
arXiv:2601.17168v1 Announce Type: new Abstract: Agentic systems have transformed how Large Language Models (LLMs) can be leveraged to create autonomous systems with goal-directed behaviors, consisting...
arXiv:2601.17172v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly capable of generating personalized, persuasive text at scale, raising new questions about bias and...
arXiv:2601.17173v1 Announce Type: new Abstract: Question answering systems are typically evaluated on factual correctness, yet many real-world applications-such as education and career guidance-require mentorship: responses...
arXiv:2601.17178v1 Announce Type: new Abstract: Hardware Trojans (HTs) remain a critical threat because learning-based detectors often overfit to narrow trigger/payload patterns and small, stylized benchmarks....
arXiv:2601.17180v1 Announce Type: new Abstract: Deep learning models for neuroimaging increasingly rely on large architectures, making efficiency a persistent concern despite advances in hardware. Through...
arXiv:2601.17181v1 Announce Type: new Abstract: Languages vary widely in how meanings map to word forms. These mappings have been found to support efficient communication; however,...
arXiv:2601.17183v1 Announce Type: new Abstract: Healthcare institutions have access to valuable patient data that could be of great help in the development of improved diagnostic...
arXiv:2601.17185v1 Announce Type: new Abstract: We propose a new method for few-shot 3D reconstruction that integrates global and local frequency regularization to stabilize geometry and...
arXiv:2601.17187v1 Announce Type: new Abstract: This work investigates the problem of quantized matrix multiplication (MatMul), which has become crucial for the efficient deployment of large...
arXiv:2601.17188v1 Announce Type: new Abstract: The unification of symbolic reasoning and neural networks remains a central challenge in artificial intelligence. Symbolic systems offer reliability and...
arXiv:2601.17189v2 Announce Type: new Abstract: We revisit benchmarks for differentially private image classification. We suggest a comprehensive set of benchmarks, allowing researchers to evaluate techniques...
arXiv:2601.17191v1 Announce Type: new Abstract: This chapter examines the global governance of artificial intelligence (AI) through the lens of the Global AI Divide, focusing on...
arXiv:2601.17192v1 Announce Type: new Abstract: Coronary microvascular dysfunction (CMD) affects millions worldwide yet remains underdiagnosed because gold-standard physiological measurements are invasive and variably reproducible. We...
arXiv:2601.17193v1 Announce Type: new Abstract: This paper studies the problem of maximizing revenue from a grid-scale battery energy storage system, accounting for uncertain future electricity...
arXiv:2601.17194v1 Announce Type: new Abstract: Social infrastructure and other built environments are increasingly expected to support well-being and community resilience by enabling social interaction. Yet...
arXiv:2601.17195v1 Announce Type: new Abstract: Low-Earth Orbit (LEO) constellations expand 5G coverage to remote regions but differ fundamentally from terrestrial networks due to rapidly changing...
arXiv:2601.17196v1 Announce Type: new Abstract: Partial Optimal Transport (POT) addresses the problem of transporting only a fraction of the total mass between two distributions, making...
arXiv:2601.17197v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated strong reasoning abilities in literal multimodal tasks such as visual mathematics and science question answering....
arXiv:2601.17198v1 Announce Type: new Abstract: This paper proposes sufficient, yet more general conditions for applying FastTwoSum as an error-free transformation (EFT) under all faithful rounding...
arXiv:2601.17203v1 Announce Type: new Abstract: Modern models for common NLP tasks often employ machine learning techniques and train on journalistic, social media, or other culturally-derived...