Weaviate Podcast Sufficient Context with Hailey Joren - Weaviate Podcast #125!
Jul 2, 2025
In this installment, Hailey Joren, a Ph.D. student at UCSD, shares her groundbreaking insights on retrieval augmented generation systems. She sheds light on the crucial difference between relevant search results and 'sufficient context' for accurate answers. With her team's innovative autorater, they tackle the future of AI, addressing how current models struggle with hallucinations. Expect discussions on fine-tuning methodologies, the role of context in AI responses, and the exciting prospects of enhancing model reliability and interpretability.
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Defining Sufficient Context
- Sufficient context differs from relevance by asking if the model should be able to answer the question given the context.
- All sufficient context is relevant, but relevant context is not necessarily sufficient.
Models Answer Despite Insufficient Context
- Models often produce correct answers even when given context insufficient to answer the question.
- Smaller models struggle to effectively use sufficient context to answer correctly.
Use Combined Signals to Abstain
- Combine sufficient context signals with model self-rated confidence to decide when to answer or abstain.
- This approach improved accuracy by over 10% in some benchmarks, outperforming using either signal alone.