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with jev, everyone is understanding the importance of calibrated confidence scores for discrete decision making we've taken that approach on…
with jev, everyone is understanding the importance of calibrated confidence scores for discrete decision making we've taken that approach one-step further and created grounded confidence scores for ge
with jev, everyone is understanding the importance of calibrated confidence scores for discrete decision making we've taken that approach one-step further and created grounded confidence scores for general schema-guided document extraction: ✅ this includes primitive types like bool, int, and float. the numbers don't have to be bounded ✅ this also includes free-form text extraction ✅ each extracted value also carries a bounding box directly back into the source document calibrated confidence scores are extremely important for human review. By setting a threshold, you can let a human reviewer audit the lower confidence values while automating the extraction of higher confidence values. If you have needs for large scale doc extraction, come check it out: https://developers.llamaindex.ai/llamaparse/extract/guides/extensions/#confidence-scores Sign up to LlamaParse here: https://cloud.llamaindex.ai/ Media Grounded Confidence is here for Extract! 🦙 When your agents and workflows depend on extracted data, you need to know how accurate that data is. We’ve added confidence scores to give you a better read on extraction accuracy, field by field. Use them to decide which results your a…
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Source: Jerry Liu (X) | 2026-09-21