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arXiv:2601.18115v1 Announce Type: new Abstract: We study the problem of learning a single neuron under standard squared loss in the presence of arbitrary label noise...
arXiv:2601.18116v1 Announce Type: new Abstract: The rapid expansion of long-context Large Language Models (LLMs) has reignited debate on whether Retrieval-Augmented Generation (RAG) remains necessary. However,...
arXiv:2601.18117v1 Announce Type: new Abstract: Decentralized decision making in multi--product firms can lead to efficiency losses when autonomous decision makers fail to internalize cross--product demand...
arXiv:2601.18118v1 Announce Type: new Abstract: Due to silence in early stages, lung cancer has been one of the most leading causes of mortality in cancer...
arXiv:2601.18119v1 Announce Type: new Abstract: SQL is central to enterprise data engineering, yet generating fully correct SQL code in a single attempt remains difficult, even...
arXiv:2601.18120v1 Announce Type: new Abstract: This paper presents a generalized weak Galerkin (gWG) finite element method for linear elasticity problems on general polygonal and polyhedral...
arXiv:2601.18121v1 Announce Type: new Abstract: Dexterous hand manipulation increasingly relies on large-scale motion datasets with precise hand-object trajectory data. However, existing resources such as DexYCB...
arXiv:2601.18123v1 Announce Type: new Abstract: Typical domestic immersion water heater systems are often operated continuously during winter, heating quickly rather than efficiently and ignoring predictable...
arXiv:2601.18125v1 Announce Type: new Abstract: Conversational agents (CAs) (e.g., chatbots) are increasingly used in settings where users disclose sensitive information, raising significant privacy concerns. Because...
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...