arXiv:2510.19316v2 Announce Type: replace
Abstract: Large Multimodal Models encode extensive factual knowledge in their pre-trained weights. However, its knowledge remains static and limited, unable to keep pace with real-world developments, which hin…
arXiv:2605.06130v1 Announce Type: new
Abstract: A persistent skill library allows language model agents to reuse successful strategies across tasks. Maintaining such a library requires three coupled capabilities. The agent selects a relevant skill, ut…
arXiv:2605.06407v1 Announce Type: cross
Abstract: Integrating speech understanding and generation is a pivotal step toward building unified speech models. However, the different representations required for these two tasks currently pose significant c…
arXiv:2605.06472v1 Announce Type: new
Abstract: LLM-based workflows compose specialized agents to execute complex tasks, and these agents usually share substantial context, allowing KV-Cache reuse to save computation. Existing approaches either manage…
A LinkedIn feature that allows paid subscribers to view a list of visitors to their profile should be made available to all EU users free of charge to comply with the region’s General Data Protection Regulation (GDPR), a legal co…
arXiv:2605.02317v2 Announce Type: replace-cross
Abstract: Adaptive optimizers such as Adam have achieved great success in training large-scale models like large language models and diffusion models. However, they often generalize worse than non-adapti…
arXiv:2605.05080v1 Announce Type: new
Abstract: We administer 45 validated psychometric questionnaires to 50 large language models (LLMs) to identify the dimensions along which LLMs differ psychometrically. Using Supervised Semantic Differential (SSD)…
arXiv:2602.02315v2 Announce Type: replace
Abstract: Large language models (LLMs) form implicit beliefs (posteriors over latent variables) from prompts, but we lack a mechanistic account of how these beliefs are encoded in representation space, how the…
arXiv:2605.04085v1 Announce Type: cross
Abstract: Objectives: Large language models (LLMs) are increasingly used for clinical text summarization, yet structured methods to assess associated patient safety risks remain limited. Failure Mode, Effects, a…
arXiv:2605.02740v2 Announce Type: replace-cross
Abstract: Evidence derived from large-scale real-world data (RWD) is increasingly informing regulatory evaluation and healthcare decision-making. Administrative claims provide population-scale, longitudi…