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This paper introduces ClinFusion, a multimodal large language model (MLLM) designed to understand medical images the way clinicians do. The
This paper shows that text placed by outsiders on public websites can sometimes end up in the data used to train large language models (LMs)
This paper studies a common blind spot in automated coding agents: they often do far more reading and checking than a task truly needs. The
This paper reviews what researchers know so far about metacognition in large language models (LLMs). Metacognition means the ability to moni
This paper presents WordVoice, a new data and model approach that lets large language model (LLM) based text-to-speech (TTS) systems control
Researchers introduce LLM-as-a-Verifier, a new way to use large language models (LLMs) to decide whether a proposed solution is correct. Ins
Large language models (LLMs) can still produce incorrect or harmful text after training. This paper studies a simple online monitor that wat
This paper studies how research ideas produced by large language models (LLMs) differ from ideas written by human researchers. Instead of ju
This paper introduces SkillComposer, a method that helps large language model (LLM) agents pick not just which skills to use but also how ma
Researchers tested a simple change to transformer language models: let some layers be narrower than others instead of making every layer the