-
We use Round-Trip Consistency (RTC) testing: generate a response, create an alternate query targeting similar content, generate second response, measure semantic similarity. This provides an automated way to evaluate temperature effectiveness without human intervention.
The classifier learns continuously from query-response patterns. In production, this reduced "hallucinations" by 42% for factual queries while improving creativity scores by 35% for open-ended tasks.
Technical details and implementation: https://github.com/codelion/adaptive-classifier
We're particularly interested in feedback from others who've dealt with temperature optimization at scale.
-
InfluxDB
InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.
Related posts
-
Show HN: An adaptive classifier that detects hallucinations in LLM/RAG outputs
-
Show HN: A classifier that learns new categories without retraining from scratch
-
A flexible, adaptive classification system for dynamic text classification
-
Adaptive Classifier: Dynamic Text Classification with Continuous Learning
-
adaptive-classifier: Cut your LLM costs with smart query routing (32.4% cost savings demonstrated)