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arXiv:2601.18127v1 Announce Type: new Abstract: Data transparency has emerged as a rallying cry for addressing concerns about AI: data quality, privacy, and copyright chief among...
arXiv:2601.18129v1 Announce Type: new Abstract: Large language models (LLMs) have progressed rapidly; however, most state-of-the-art models are trained and evaluated primarily in high-resource languages such...
arXiv:2601.18130v1 Announce Type: new Abstract: Mixture-of-Agents (MoA) improves LLM performance through layered collaboration, but its dense topology raises costs and latency. Existing methods employ LLM...
arXiv:2601.18132v1 Announce Type: new Abstract: Missed and delayed diagnosis remains a major challenge in rare disease care. At the initial clinical encounters, physicians assess rare...
arXiv:2601.18134v1 Announce Type: new Abstract: Broadcast distribution of updates (e.g., security patches, machine learning models) from a server to end devices (EDs) is a critical...
arXiv:2601.18135v1 Announce Type: new Abstract: As a crucial element of public security, video anomaly detection (VAD) aims to measure deviations from normal patterns for various...
arXiv:2601.18137v1 Announce Type: new Abstract: While agent evaluation has shifted toward long-horizon tasks, most benchmarks still emphasize local, step-level reasoning rather than the global constrained...
arXiv:2601.18140v1 Announce Type: new Abstract: RTL simulation on CPUs remains a persistent bottleneck in hardware design. State-of-the-art simulators embed the circuit directly into the simulation...
arXiv:2601.18142v1 Announce Type: new Abstract: Safe reinforcement learning (Safe RL) seeks to maximize rewards while satisfying safety constraints, typically addressed through Lagrangian-based methods. However, existing...
arXiv:2601.18146v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly applied to ranking tasks in retrieval and recommendation. Although reasoning prompting can enhance ranking...
arXiv:2601.18148v1 Announce Type: new Abstract: Space exploration missions generate rapidly increasing volumes of scientific telemetry that far exceed the capacity of today's manually scheduled, RF-based...
arXiv:2601.18150v1 Announce Type: new Abstract: Reinforcement learning (RL) for large language models (LLMs) is increasingly bottlenecked by rollout (generation), where long output sequence lengths make...
arXiv:2601.18151v1 Announce Type: new Abstract: In social recommenders, the inherent nonlinearity and opacity of synergistic effects across multiple social networks hinders users from understanding how...
arXiv:2601.18154v1 Announce Type: new Abstract: Endometriosis ultrasound reports are often unstructured free-text documents that require manual abstraction for downstream tasks such as analytics, machine learning...
arXiv:2601.18156v1 Announce Type: new Abstract: Key doctrines, including novelty (patent), originality (copyright), and distinctiveness (trademark), turn on a shared empirical question: whether a body of...
arXiv:2601.18157v1 Announce Type: new Abstract: The advent of always-on personal AI assistants, enabled by all-day wearable devices such as smart glasses, demands a new level...
arXiv:2601.18158v1 Announce Type: new Abstract: Graphs are central to modeling relationships in scientific computing, data analysis, and AI/ML, but their growing scale can exceed the...
arXiv:2601.18159v1 Announce Type: new Abstract: The growing demand for compute-intensive applications has made multi-chiplet architectures a promising alternative to monolithic designs, offering improved scalability and...
arXiv:2601.18162v1 Announce Type: new Abstract: Fine-grained emotion recognition is a challenging multi-label NLP task due to label overlap and class imbalance. In this work, we...
arXiv:2601.18168v1 Announce Type: new Abstract: Transarterial chemoembolization (TACE) is a preferred treatment option for hepatocellular carcinoma and other liver malignancies, yet it remains a highly...
arXiv:2601.18171v1 Announce Type: new Abstract: Unsupervised Domain Adaptation (UDA) aims to mitigate performance degradation when training and testing data are sampled from different distributions. While...
arXiv:2601.18172v1 Announce Type: new Abstract: One-stage object detection, particularly the YOLO series, strikes a favorable balance between accuracy and efficiency. However, existing YOLO detectors lack...
arXiv:2601.18175v1 Announce Type: new Abstract: A widely used technique for improving policies is success conditioning, in which one collects trajectories, identifies those that achieve a...
arXiv:2601.18177v1 Announce Type: new Abstract: Silent speech interfaces (SSIs) enable silent interaction in noise-sensitive or privacy-sensitive settings. However, existing SSIs face practical deployment trade-offs among...