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cs.CL2026
QAQ: Bidirectional Semantic Coherence for Selecting High-Quality Synthetic Code Instructions
Jiayin Lei, Ming Ma, Yunxi Duan +2
Synthetic data has become essential for training code generation models, yet it introduces significant noise and hallucinations that are difficult to detect with current metrics. E…
cs.CL2019
Pre-train and Plug-in: Flexible Conditional Text Generation with Variational Auto-Encoders
Yu Duan, Canwen Xu, Jiaxin Pei +2
Conditional Text Generation has drawn much attention as a topic of Natural Language Generation (NLG) which provides the possibility for humans to control the properties of generate…