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arXiv:2507.00310v3 Announce Type: replace Abstract: The promise of autonomous scientific discovery (ASD) hinges not only on answering questions, but also on knowing which questions to...
arXiv:2506.23242v4 Announce Type: replace Abstract: This paper revisits the classical formulation of the Z-transform and its relationship to the inverse Laplace transform (L-1), originally developed...
arXiv:2506.21078v2 Announce Type: replace Abstract: Integrated sensing and communications (ISAC) is considered a key enabler to support application scenarios such as the Internet-of-Things (IoT) in...
arXiv:2506.20221v3 Announce Type: replace Abstract: Motivated by the theory of proof complexity generators we consider the following $\Sigma^p_2$ search problem $\mbox{DD}_P$ determined by a propositional...
arXiv:2506.20063v4 Announce Type: replace Abstract: Background: Software development teams are increasingly diverse, embedded, and cross-disciplinary. Domain experts (DEs) from different disciplines collaborate with professional software...
arXiv:2506.19054v3 Announce Type: replace Abstract: As LLMs become widespread across diverse applications, concerns about the security and safety of LLM interactions have intensified. Numerous guardrail...
arXiv:2506.17507v2 Announce Type: replace Abstract: In the noisy primitives model, each primitive comparison performed by an algorithm, e.g., testing whether one value is greater than...
arXiv:2506.09394v3 Announce Type: replace Abstract: The randomized coordinate descent (RCD) method is a classical algorithm with simple, lightweight iterations that is widely used for various...
arXiv:2506.06119v2 Announce Type: replace Abstract: Due to the increasing threat of attacks on satellite systems, novel countermeasures have been developed to provide additional security. Among...
arXiv:2506.06006v2 Announce Type: replace Abstract: Can unified vision-language models (VLMs) perform forward dynamics prediction (FDP), i.e., predicting the future state (in image form) given the...
arXiv:2506.04755v2 Announce Type: replace Abstract: While multi-modal large language models (MLLMs) have made significant progress in complex reasoning tasks via reinforcement learning, it is commonly...
arXiv:2506.03914v3 Announce Type: replace Abstract: Data augmentation is a powerful mechanism in equivariant machine learning, encouraging symmetry by training networks to produce consistent outputs under...
arXiv:2506.03527v2 Announce Type: replace Abstract: Accurately evaluating scholarly influence is essential for fair academic assessment, yet traditional bibliometric indicators - dominated by publication and citation...
arXiv:2506.00058v2 Announce Type: replace Abstract: The rise of large language models (LLMs) has created a new job role: the Prompt Engineer. Despite growing interest in...
arXiv:2505.24262v2 Announce Type: replace Abstract: Model editing techniques, particularly task arithmetic with task vectors, offer an efficient alternative to full fine-tuning by enabling direct parameter...
arXiv:2505.20457v2 Announce Type: replace Abstract: Elliptic Partial Differential Equations (PDEs) play a central role in computing the equilibrium conditions of physical problems (heat, gravitation, electrostatics,...
arXiv:2505.20123v3 Announce Type: replace Abstract: Diffusion distillation provides an effective approach for learning lightweight and few-steps diffusion models with efficient generation. However, evaluating their generalization...
arXiv:2505.18382v4 Announce Type: replace Abstract: Pre-trained large language models (LLMs) show promise for robotic task planning but often struggle to guarantee correctness in long-horizon problems....
arXiv:2505.16348v3 Announce Type: replace Abstract: LLM-powered embodied agents have shown success on conventional object-rearrangement tasks, but providing personalized assistance that leverages user-specific knowledge from past...
arXiv:2505.13557v2 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) systems are widely used in question-answering (QA) tasks, but current benchmarks lack metadata integration, limiting their evaluation...
arXiv:2505.13430v3 Announce Type: replace Abstract: As the size of large language models grows exponentially, GPU memory has become a bottleneck for adapting these models to...
arXiv:2505.12977v3 Announce Type: replace Abstract: In model predictive control (MPC), the choice of cost-weighting matrices and designing the Hessian matrix directly affects the trade-off between...
arXiv:2505.12424v3 Announce Type: replace Abstract: Search-Based Software Testing (SBST) is a well-established approach for automated unit test generation, yet it often suffers from premature convergence...
arXiv:2505.10297v3 Announce Type: replace Abstract: Federated learning (FL) remains highly vulnerable to adaptive backdoor attacks that preserve stealth by closely imitating benign update statistics. Existing...