Firehose

This paper introduces a system called EMBL AI Librarian that helps AI agents find relevant life-science papers and evidence by providing a natural language interface. Practitioners in life sciences and AI development may care about this paper because it shows how a better knowledge retrieval system can improve the performance of AI agents in various tasks.

This paper introduces a framework to audit system prompts in AI applications, examining how developers design and use these prompts to govern the behaviors of foundation models. Practitioners should care because the lack of transparency and accountability in system prompts can erode trust in AI systems.

This paper investigates how AI-assisted coding assistants can better understand and respond to users' ambiguous coding requests by leveraging their past experiences. A practitioner might care about developing more effective coding assistants that can reduce the need for repeated clarification.

This paper introduces a new approach to agentic speech recognition that uses a memory to help correct mistakes and improve accuracy. By limiting the corrections made, the system can avoid over-correcting and improve performance on challenging tasks.