9 citations · 9 across the 2 of their papers we have counts for
2 papers
cs.SE2023★ 9 cited
ClarifyGPT: Empowering LLM-based Code Generation with Intention Clarification
Fangwen Mu, Lin Shi, Song Wang +5
We introduce a novel framework named ClarifyGPT, which aims to enhance code generation by empowering LLMs with the ability to identify ambiguous requirements and ask targeted clari…
cs.CL2023
LiteG2P: A fast, light and high accuracy model for grapheme-to-phoneme conversion
Chunfeng Wang, Peisong Huang, Yuxiang Zou +4
As a key component of automated speech recognition (ASR) and the front-end in text-to-speech (TTS), grapheme-to-phoneme (G2P) plays the role of converting letters to their correspo…