LLM Distillation and Comment Bursting Reshape Cerebras Knowledge Base Retrieval

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A developer rebuilding the Cerebras knowledge base applied two techniques — LLM distillation and comment bursting — to improve retrieval quality across over 3,000 issue threads. Distillation rewrote each thread into a structured question-and-answer document, successfully processing 2,542 of 3,002 threads, while the remaining 15% fell back to raw content. Comment bursting extracted high-signal individual comments into separate vector rows, expanding the corpus from roughly 3,700 to over 16,000 documents. Despite these changes, most retrieval metrics declined, with MRR dropping from 0.77 to 0.63 for vector search, largely because distillation discarded verbatim error strings that keyword search had previously relied on. The one positive outcome was hybrid recall@10 improving from 0.90 to 0.94, a result the author flags as significant for the next stage of the project.

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