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4 papers published across 1 lab.
Multimodal LLMs struggle to pinpoint objects from nouns alone, but SWIM training realigns vision and language to outperform visual-prompt methods.
Current personal assistant agents struggle to anticipate and act on unstated user needs in long, complex workflows, revealing a critical gap between task completion and genuine proactivity.
Forget hand-engineered features: this work shows how to train LLMs to predict clinical events directly from unstructured notes, achieving surprisingly strong results.
AI's promise to revolutionize pharma is tempered by the urgent need for explainable, validated models that can navigate regulatory hurdles and ethical concerns.