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cs.LG2025
Advancing Semantic Caching for LLMs with Domain-Specific Embeddings and Synthetic Data
Waris Gill, Justin Cechmanek, Tyler Hutcherson +5
This report investigates enhancing semantic caching effectiveness by employing specialized, fine-tuned embedding models. Semantic caching relies on embedding similarity rather than…
cs.AI2025
Ensemble based approach to quantifying uncertainty of LLM based classifications
Srijith Rajamohan, Ahmed Salhin, Josh Frazier +3
The output of Large Language Models (LLMs) are a function of the internal model's parameters and the input provided into the context window. The hypothesis presented here is that u…