2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.SD2025
Bridging the gap between training and inference in LM-based TTS models
Ruonan Zhang, Lingzhou Mu, Xixin Wu +1
Recent advancements in text-to-speech (TTS) have shown that language model (LM) based systems offer competitive performance compared to traditional approaches. However, in training…
cs.CL2024★ 1 cited
A Survey on the Honesty of Large Language Models
Siheng Li, Cheng Yang, Taiqiang Wu +12
Honesty is a fundamental principle for aligning large language models (LLMs) with human values, requiring these models to recognize what they know and don't know and be able to fai…
cs.CL2021★ 2 cited
Attention Forcing for Machine Translation
Qingyun Dou, Yiting Lu, Potsawee Manakul +2
Auto-regressive sequence-to-sequence models with attention mechanisms have achieved state-of-the-art performance in various tasks including Text-To-Speech (TTS) and Neural Machine…