arXiv:2604.06208v1 Announce Type: cross
Abstract: A significant amount of data held in Oncology Electronic Medical Records (EMRs) is contained in unstructured provider notes — including but not limited to the chemotherapy (or cancer treatment) outcom…
arXiv:2604.07349v1 Announce Type: cross
Abstract: Exact relevance certification asks which coordinates are necessary to determine the optimal action in a coordinate-structured decision problem. The tractable families treated here admit a finite primit…
arXiv:2604.06207v1 Announce Type: cross
Abstract: This paper investigates demonstration selection strategies for predicting a user’s next point-of-interest (POI) using large language models (LLMs), aiming to accurately forecast a user’s subsequent loc…
arXiv:2604.07320v1 Announce Type: cross
Abstract: Low-resource languages pose a challenge for machine translation with large language models (LLMs), which require large amounts of training data. One potential way to circumvent this data dependence is …
arXiv:2604.06206v1 Announce Type: cross
Abstract: This study seeks to uncover evidence of a latent structure in evolved human culture as it is refracted through contemporary large language models (LLMs). Drawing on parallel responses from six leading …
arXiv:2604.07277v1 Announce Type: cross
Abstract: Online reinforcement learning (RL) serves as an effective method for enhancing the capabilities of Android agents. However, guiding agents to learn through online interaction is prohibitively expensive…
arXiv:2604.06205v1 Announce Type: cross
Abstract: The growth of online platforms and user content requires strong content moderation systems that can handle complex inputs from various media types. While large language models (LLMs) are effective, the…
arXiv:2604.07253v1 Announce Type: cross
Abstract: In gender-restrictive and surveilled contexts, where access to formal education may be restricted for women, pursuing education involves safety and privacy risks. When women are excluded from schools a…
arXiv:2604.06204v1 Announce Type: cross
Abstract: Personalization is essential for Large Language Model (LLM)-based agents to adapt to users’ preferences and improve response quality and task performance. However, most existing approaches infer person…
arXiv:2604.07190v1 Announce Type: cross
Abstract: We present a comprehensive adoption snapshot of the leading open language models and who is building them, focusing on the ~1.5K mainline open models from the likes of Alibaba’s Qwen, DeepSeek, Meta’s …