arXiv:2604.01538v1 Announce Type: new
Abstract: Large language models have been adopted in the medical domain for clinical documentation to reduce clinician burden. However, studies have reported that LLMs often “forget” a significant amount of instru…
arXiv:2604.02194v1 Announce Type: new
Abstract: Retrieval-Augmented Language Models (RALMs) have demonstrated significant potential in knowledge-intensive tasks; however, they remain vulnerable to performance degradation when presented with irrelevant…
arXiv:2604.02217v1 Announce Type: cross
Abstract: Understanding how Large Language Models (LLMs) process information from prompts remains a significant challenge. To shed light on this “black box,” attention visualization techniques have been develope…
arXiv:2410.17954v2 Announce Type: replace-cross
Abstract: Sparse Mixture-of-Experts (MoE) models can outperform dense large language models at similar computation by activating only a small set of experts per token. However, stacking many expert modul…
arXiv:2604.01705v1 Announce Type: new
Abstract: Automatic speech recognition (ASR) is a critical interface for human-AI interaction in gastrointestinal endoscopy, yet its reliability in real-world clinical settings is limited by domain-specific termin…
arXiv:2507.05660v2 Announce Type: replace-cross
Abstract: Customizing Large Language Models (LLMs) on untrusted datasets poses severe risks of injecting toxic behaviors. In this work, we introduce Optimus, a novel defense framework designed to mitigat…
arXiv:2603.20673v2 Announce Type: replace
Abstract: Retrieval-augmented language models can retrieve relevant evidence yet still commit to answers before explicitly checking whether the retrieved context supports the conclusion. We present PAVE (Premi…
arXiv:2509.17608v2 Announce Type: replace-cross
Abstract: Social narratives help autistic children understand and navigate social situations through stories. To ensure effective practice, however, they often require significant time and effort from pa…
arXiv:2505.15062v4 Announce Type: replace
Abstract: Knowledge extrapolation is the process of inferring novel information by combining and extending existing knowledge that is explicitly available. It is essential for solving complex questions in spec…
arXiv:2603.21736v2 Announce Type: replace-cross
Abstract: Different types of reasoning impose different structural demands on representational systems, yet no systematic account of these demands exists across psychology, AI, and philosophy of mind. I …