Optimizing Retrieval Agents with Shirley Wu - Weaviate Podcast #115!
Hey everyone! Thank you so much for watching the 115th episode of the Weaviate Podcast featuring Shirley Wu from Stanford University!
We explore the innovative Avatar Optimizer—a novel framework that leverages contrastive reasoning to refine LLM agent prompts for optimal tool usage. Shirley explains how this self-improving system evolves through iterative feedback by contrasting positive and negative examples, enabling agents to handle complex tasks more effectively.
We also dive into the STaRK Benchmark, a comprehensive testbed designed to evaluate retrieval systems on semi-structured…
The skinny
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