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arXiv:2508.19057v2 Announce Type: replace Abstract: Triangle counting is a fundamental problem in graph mining, essential for analyzing graph streams with arbitrary edge orders. However, exact...
arXiv:2508.19065v3 Announce Type: replace Abstract: Privacy regulations require the erasure of data from deep learning models. This is a significant challenge that is amplified in...
arXiv:2508.19151v2 Announce Type: replace Abstract: Dense Associative Memory (DAM) models have been attracting renewed attention since they were shown to be robust to adversarial examples...
arXiv:2508.20697v2 Announce Type: replace Abstract: As large language models (LLMs) continue to grow in capability, so do the risks of harmful misuse through fine-tuning. While...
arXiv:2509.01387v2 Announce Type: replace Abstract: Understanding fine-grained links between documents is crucial for many applications, yet progress is limited by the lack of efficient methods...
arXiv:2509.02417v2 Announce Type: replace Abstract: The emergence of 6G wireless communication enables massive edge device access and supports real-time intelligent services such as the Internet...
arXiv:2509.04058v2 Announce Type: replace Abstract: Stylized motion generation is actively studied in computer graphics, especially benefiting from the rapid advances in diffusion models. The goal...
arXiv:2509.04472v3 Announce Type: replace Abstract: Understanding user intent is essential for effective planning in conversational assistants, particularly those powered by large language models (LLMs) coordinating...
arXiv:2509.05372v2 Announce Type: replace Abstract: Large Language Model (LLM) - based Automated Program Repair (APR) systems are increasingly integrated into modern software development workflows, offering...
arXiv:2509.06752v2 Announce Type: replace Abstract: This Survey provides an overview of techniques in termination analysis for programs with numerical variables and transitions defined by linear...
arXiv:2509.06822v2 Announce Type: replace Abstract: The advent of complex, interconnected long-horizon LLM systems has made it incredibly tricky to identify where and when these systems...
arXiv:2509.07363v3 Announce Type: replace Abstract: As a promising 6G enabler beyond conventional bit-level transmission, semantic communication can considerably reduce required bandwidth resources, while its combination...
arXiv:2509.07378v3 Announce Type: replace Abstract: The rise of Internet of Things (IoT) devices has led to the development of numerous time-sensitive applications that require quick...
arXiv:2509.07593v2 Announce Type: replace Abstract: End-to-end reinforcement learning (RL) for motion control trains policies directly from sensor inputs to motor commands, enabling unified controllers for...
arXiv:2509.08404v2 Announce Type: replace Abstract: Massive Open Online Courses (MOOCs) have become increasingly popular worldwide. However, learners primarily rely on watching videos, easily losing knowledge...
arXiv:2509.08604v4 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated significant potential in medicine, with many studies adapting them through continued pre-training or fine-tuning...
arXiv:2509.08625v4 Announce Type: replace Abstract: The silhouette coefficient quantifies, for each observation, the balance between within-cluster cohesion and between-cluster separation, taking values in the range...
arXiv:2509.09071v4 Announce Type: replace Abstract: Markets increasingly accommodate large language models (LLMs) as autonomous decision-making agents. As this transition occurs, it becomes critical to evaluate...
arXiv:2509.09828v3 Announce Type: replace Abstract: Robust semantic perception for autonomous vehicles relies on effectively combining multiple sensors with complementary strengths and weaknesses. State-of-the-art sensor fusion...
arXiv:2509.09840v3 Announce Type: replace Abstract: AI capabilities for document reader software are usually presented in separate chat interfaces. We explore integrating AI into document comments,...
arXiv:2509.10414v3 Announce Type: replace Abstract: In-context learning (ICL) allows some autoregressive models to solve tasks via next-token prediction and without needing further training. This has...
arXiv:2509.10950v3 Announce Type: replace Abstract: Generative AI (GenAI) is reshaping work, but adoption remains largely individual and experimental rather than coordinated into collaborative work. Whether...
arXiv:2509.11480v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have emerged as powerful generalist policies for robotic control, yet their performance scaling across model architectures and...
arXiv:2509.11602v2 Announce Type: replace Abstract: A Straight-Line Program (SLP) for a string $T$ is a context-free grammar in Chomsky normal form that derives $T$ only,...