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20232026
most citedBoosting Large Language Model for Speech Synthesis: An Empirical Study

2 citations · 5 across the 11 of their papers we have counts for

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cs.CL2026

MARCH: Multi-Agent Reinforced Self-Check for LLM Hallucination

Zhuo Li, Yupeng Zhang, Pengyu Cheng +8

Hallucination remains a critical bottleneck for large language models (LLMs), undermining their reliability in real-world applications, especially in Retrieval-Augmented Generation…

cs.CL2024

Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey

Liang Chen, Zekun Wang, Shuhuai Ren +24

Building on the foundations of language modeling in natural language processing, Next Token Prediction (NTP) has evolved into a versatile training objective for machine learning ta…

cs.CL2024

Autoregressive Speech Synthesis without Vector Quantization

Lingwei Meng, Long Zhou, Shujie Liu +9

We present MELLE, a novel continuous-valued token based language modeling approach for text-to-speech synthesis (TTS). MELLE autoregressively generates continuous mel-spectrogram f…

cs.CL2024★ 2 cited

WavLLM: Towards Robust and Adaptive Speech Large Language Model

Shujie Hu, Long Zhou, Shujie Liu +9

The recent advancements in large language models (LLMs) have revolutionized the field of natural language processing, progressively broadening their scope to multimodal perception…

cs.CL2023★ 2 cited

Boosting Large Language Model for Speech Synthesis: An Empirical Study

Hongkun Hao, Long Zhou, Shujie Liu +4

Large language models (LLMs) have made significant advancements in natural language processing and are concurrently extending the language ability to other modalities, such as spee…