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cs.CL2024
Unlocking the Power of GANs in Non-Autoregressive Text Generation
Da Ren, Yi Cai, Qing Li
Generative Adversarial Networks (GANs) have been studied in text generation to tackle the exposure bias problem. Despite their remarkable development, they adopt autoregressive str…
cs.CL2024
LLaMA-E: Empowering E-commerce Authoring with Object-Interleaved Instruction Following
Kaize Shi, Xueyao Sun, Dingxian Wang +3
E-commerce authoring entails creating engaging, diverse, and targeted content to enhance preference elicitation and retrieval experience. While Large Language Models (LLMs) have re…