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arXiv:2601.02243v2 Announce Type: replace Abstract: We develop a mathematical framework for the optimal scheduling of flexible water desalination plants (WDPs) as hybrid generator-load resources. WDPs...
arXiv:2601.02278v2 Announce Type: replace Abstract: Three-phase asynchronous motor are fundamental components in industrial systems, and their failure can lead to significant operational downtime and economic...
arXiv:2601.02885v2 Announce Type: replace Abstract: Defining agency is an extremely important challenge for cognitive science and artificial intelligence. Physics generally describes mechanical happenings, but there...
arXiv:2601.03596v2 Announce Type: replace Abstract: Few-shot segmentation (FSS) aims to rapidly learn novel class concepts from limited examples to segment specific targets in unseen images,...
arXiv:2601.04301v2 Announce Type: replace Abstract: As frontier AI systems are pretrained on web-scale data, test set contamination has become a critical concern for accurately assessing...
arXiv:2601.08052v2 Announce Type: replace Abstract: Dairy farming is an energy intensive sector that relies heavily on grid electricity. With increasing renewable energy integration, sustainable energy...
arXiv:2601.08118v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used as human simulators, both for evaluating conversational systems and for generating fine-tuning data....
arXiv:2601.08414v3 Announce Type: replace Abstract: Real-time multi-camera 3D reconstruction is crucial for 3D perception, immersive interaction, and robotics. Existing methods struggle with multi-view fusion, camera...
arXiv:2601.08776v3 Announce Type: replace Abstract: Cycle-Consistent Adversarial Network (CycleGAN) is very promising in domain adaptation. In this report, an example in medical domain will be...
arXiv:2601.09347v2 Announce Type: replace Abstract: We study the problem of maximizing R{\'e}nyi entropy of order $2$ (equivalently, minimizing the index of coincidence) over the set...
arXiv:2601.14327v2 Announce Type: replace Abstract: Although Mixture-of-Experts (MoE) Large Language Models (LLMs) deliver superior accuracy with a reduced number of active parameters, their pre-training represents...
arXiv:2601.16393v2 Announce Type: replace Abstract: This paper presents a terrestrial GNSS-based orbit and clock estimation framework for lunar navigation satellites. To enable high-precision estimation under...
arXiv:2601.17053v2 Announce Type: replace Abstract: Physical activity during hip fracture rehabilitation is essential for mitigating long-term functional decline in geriatric patients. However, it is rarely...
arXiv:2601.17815v2 Announce Type: replace Abstract: Imitation learning provides a powerful framework for goal-conditioned visual navigation in mobile robots, enabling obstacle avoidance while respecting human preferences...
arXiv:2601.18226v2 Announce Type: replace Abstract: Conventional agent systems often struggle in open-ended environments where task distributions continuously drift and external supervision is scarce. Their reliance...
arXiv:2601.18282v2 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated remarkable capabilities in function calling for autonomous agents, yet current mechanisms lack explicit reasoning...
arXiv:2601.18642v2 Announce Type: replace Abstract: Large language models deployed as autonomous agents face critical memory limitations, lacking selective forgetting mechanisms that lead to either catastrophic...
arXiv:2601.18778v2 Announce Type: replace Abstract: Can a model learn to escape its own learning plateau? Reinforcement learning methods for finetuning large reasoning models stall on...
arXiv:2601.19154v2 Announce Type: replace Abstract: Shuffling is a powerful way to amplify privacy of a local randomizer in private distributed data analysis, but existing analyses...
arXiv:2601.19304v2 Announce Type: replace Abstract: Spoken English proficiency is a powerful driver of economic mobility for low-income Indian youth, yet opportunities for spoken practice remain...
arXiv:2601.19311v2 Announce Type: replace Abstract: As large language models become integral to agentic artificial intelligence systems, their energy demands during inference may pose significant sustainability...
arXiv:2601.19585v2 Announce Type: replace Abstract: Interactive recommender systems can dynamically adapt to user feedback, but often suffer from content homogeneity and filter bubble effects due...
arXiv:2601.19791v2 Announce Type: replace Abstract: We study grokking, the onset of generalization long after overfitting, in a classical ridge regression setting. We prove end-to-end grokking...
arXiv:2601.21112v2 Announce Type: replace Abstract: Frontier language model agents can exhibit misaligned behaviors, including deception, exploiting reward hacks, and pursuing hidden objectives. To control potentially...