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cs.CL2023
DiNADO: Norm-Disentangled Neurally-Decomposed Oracles for Controlling Language Models
Sidi Lu, Wenbo Zhao, Chenyang Tao +4
NeurAlly-Decomposed Oracle (NADO) is a powerful approach for controllable generation with large language models. It is designed to avoid catastrophic forgetting while achieving gua…
cs.CL2023
Exploring Energy-based Language Models with Different Architectures and Training Methods for Speech Recognition
Hong Liu, Zhaobiao Lv, Zhijian Ou +2
Energy-based language models (ELMs) parameterize an unnormalized distribution for natural sentences and are radically different from popular autoregressive language models (ALMs).…
cs.CL2023
Unsupervised Melody-to-Lyric Generation
Yufei Tian, Anjali Narayan-Chen, Shereen Oraby +8
Automatic melody-to-lyric generation is a task in which song lyrics are generated to go with a given melody. It is of significant practical interest and more challenging than uncon…