Speed and Scalability: Unlike traditional AI systems requiring extensive training data, Smart Intents deliver higher accuracy with just a concise description. They eliminate the need to maintain vast libraries of examples, allowing you to adapt and scale your automated messaging efficiently. Consistent ...
Our results are promising with using the OpenAI Codex LLM on MBPP: our best algorithm improves the pass@1 code generation accuracy metric from 48.39% to 70.49% with a single user query, and up to 85.48% with up to 5 user queries. Second, we can generate a non-tr...
With the development of PLMs and LLMs, many downstream tasks are organized as end-to-end processing tasks to achieve higher accuracy and mitigate error propagation issues. However, we can still observe that NER can improve the explainability in recommendation and dialogue systems [468,478], which...
and compare their relative effectiveness on the MBPP academic code generation benchmark. Our results are promising with using the OpenAI Codex LLM on MBPP: our best algorithm improves the pass@1 code generation accuracy metric from 48.39% to 70.49% with a single user query, and up...