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arXiv:2601.18641v2 Announce Type: replace Abstract: Speech remains one of the most visible yet overlooked vectors of inclusion and exclusion in contemporary society. While fluency is...
arXiv:2601.18823v2 Announce Type: replace Abstract: Variational autoencoders (VAE) encode data into lower-dimensional latent vectors before decoding those vectors back to data. Once trained, one can...
arXiv:2601.18842v2 Announce Type: replace Abstract: GUI agents enable end-to-end automation through direct perception of and interaction with on-screen interfaces. However, these agents frequently access interfaces...
arXiv:2601.18973v2 Announce Type: replace Abstract: Quantum hardware suffers from intrinsic device heterogeneity and environmental drift, forcing practitioners to choose between suboptimal non-adaptive controllers or costly...
arXiv:2601.18987v3 Announce Type: replace Abstract: Determining whether a program terminates is a central problem in computer science. Turing's foundational result established the Halting Problem as...
arXiv:2601.19085v2 Announce Type: replace Abstract: Biological neural systems must be fast but are energy-constrained. Evolution's solution: act on the first signal. Winner-take-all circuits and time-to-first-spike...
arXiv:2601.19092v2 Announce Type: replace Abstract: Scaling modern deep learning workloads demands coordinated placement of data and compute across device meshes, memory hierarchies, and heterogeneous accelerators....
arXiv:2601.19107v2 Announce Type: replace Abstract: Machine learning education faces a fundamental gap: students learn algorithms without understanding the systems that execute them. They study gradient...
arXiv:2601.19120v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly used to generate natural-language explanations in recommender systems, acting as explanation agents that reason...
arXiv:2601.19121v2 Announce Type: replace Abstract: Recommendation systems must optimize multiple objectives while satisfying hard business constraints such as fairness and coverage. For example, an e-commerce...
arXiv:2601.19139v2 Announce Type: replace Abstract: The growing adoption of Apple Silicon for machine learning development has created demand for efficient inference solutions that leverage its...
arXiv:2601.19284v2 Announce Type: replace Abstract: Stabilizing a dynamical system is a fundamental problem that serves as a cornerstone for many complex tasks in the field...
arXiv:2601.19402v2 Announce Type: replace Abstract: Production LLM deployments serve diverse workloads where cost and quality requirements vary by customer tier, time of day, and query...
arXiv:2601.19423v2 Announce Type: replace Abstract: Large language models have recently shown promise for multimodal recommendation, particularly with text and image inputs. Yet real-world recommendation signals...
arXiv:2601.19494v2 Announce Type: replace Abstract: High-quality evaluation benchmarks are pivotal for deploying Large Language Models (LLMs) in Automated Code Review (ACR). However, existing benchmarks suffer...
arXiv:2601.19501v2 Announce Type: replace Abstract: Generative recommendation (GR) typically first quantizes continuous item embeddings into multi-level semantic IDs (SIDs), and then generates the next item...
arXiv:2601.19510v2 Announce Type: replace Abstract: Large Language Models (LLMs) have recently empowered agentic frameworks to exhibit advanced reasoning and planning capabilities. However, their integration in...
arXiv:2601.19647v2 Announce Type: replace Abstract: In recent years, applications such as real-time simulations, autonomous systems, and video games increasingly demand the processing of complex geometric...
arXiv:2601.19657v2 Announce Type: replace Abstract: Diffusion Language Models (DLMs) have emerged as a compelling alternative to autoregressive approaches, enabling parallel text generation with competitive performance....
arXiv:2601.19684v2 Announce Type: replace Abstract: User authentication and fraud detection face growing challenges as digital systems expand and adversaries adopt increasingly sophisticated tactics. Traditional knowledge-based...
arXiv:2601.19768v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly paired with activation-based monitoring to detect and prevent harmful behaviors that may not be...
arXiv:2601.19876v2 Announce Type: replace Abstract: Extensive studies suggested that fluid mechanical markers of intracranial aneurysms (IAs) derived from Computational Fluid Dynamics (CFD) can indicate disease...
arXiv:2601.19965v2 Announce Type: replace Abstract: In industrial recommender systems, conversion rate (CVR) is widely used for traffic allocation, but it fails to fully reflect recommendation...
arXiv:2601.19967v2 Announce Type: replace Abstract: Collecting web data to train deep models has become increasingly common, raising concerns about unauthorized data usage. To mitigate this...