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arXiv:2604.06213v1 Announce Type: new Abstract: Large Language Models (LLMs) excel at human-like language generation but often embed and amplify implicit, intersectional biases, especially under persona-driven …
Law professor Andrew Guthrie Ferguson chats with Ars about his new book,Your Data Will Be Used Against You.
Any tanker passing must reveal its cargo so Iran can determine transit fee amount.
arXiv:2604.06610v1 Announce Type: new Abstract: Decentralised online learning enables runtime adaptation in cyber-physical multi-agent systems, but when operating conditions change, learned policies often require substantial …
arXiv:2604.06374v1 Announce Type: new Abstract: Latent reasoning via continuous chain-of-thoughts (Latent CoT) has emerged as a promising alternative to discrete CoT reasoning. Operating in continuous …
arXiv:2604.06193v1 Announce Type: new Abstract: Depression is underdiagnosed in primary care, yet timely identification remains critical. Recorded clinical encounters, increasingly common with digital scribing technologies, …
arXiv:2604.06205v1 Announce Type: new Abstract: The growth of online platforms and user content requires strong content moderation systems that can handle complex inputs from various …
arXiv:2604.06330v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have achieved rapid progress, viewed as a promising alternative to the autoregressive paradigm. However, most …
arXiv:2604.06207v1 Announce Type: new Abstract: This paper investigates demonstration selection strategies for predicting a user's next point-of-interest (POI) using large language models (LLMs), aiming to …
arXiv:2604.06551v1 Announce Type: new Abstract: Large language models show potential for scalable mental-health support by simulating Cognitive Behavioral Therapy (CBT) counselors. However, existing methods often …
arXiv:2604.06365v1 Announce Type: new Abstract: Arabic medical text generation is increasingly needed to help users interpret symptoms and access general health guidance in their native …
arXiv:2604.06543v1 Announce Type: new Abstract: In this work, we demonstrate that reliable stochastic sampling is a fundamental yet unfulfilled requirement for Large Language Models (LLMs) …