Zobrazeno 1 - 10
of 505
pro vyhledávání: '"Hu, YuXuan"'
Autor:
Chen, Wenxi, Ma, Ziyang, Yan, Ruiqi, Liang, Yuzhe, Li, Xiquan, Xu, Ruiyang, Niu, Zhikang, Zhu, Yanqiao, Yang, Yifan, Liu, Zhanxun, Yu, Kai, Hu, Yuxuan, Li, Jinyu, Lu, Yan, Liu, Shujie, Chen, Xie
Recent advancements highlight the potential of end-to-end real-time spoken dialogue systems, showcasing their low latency and high quality. In this paper, we introduce SLAM-Omni, a timbre-controllable, end-to-end voice interaction system with single-
Externí odkaz:
http://arxiv.org/abs/2412.15649
Autor:
Yang, Yifan, Ma, Ziyang, Liu, Shujie, Li, Jinyu, Wang, Hui, Meng, Lingwei, Sun, Haiyang, Liang, Yuzhe, Xu, Ruiyang, Hu, Yuxuan, Lu, Yan, Zhao, Rui, Chen, Xie
This paper introduces Interleaved Speech-Text Language Model (IST-LM) for streaming zero-shot Text-to-Speech (TTS). Unlike many previous approaches, IST-LM is directly trained on interleaved sequences of text and speech tokens with a fixed ratio, eli
Externí odkaz:
http://arxiv.org/abs/2412.16102
Integrating speech into LLM (speech-LLM) has gaining increased attention recently. The mainstream solution is to connect a well-trained speech encoder and LLM with a neural adapter. However, the length mismatch between the speech and text sequences a
Externí odkaz:
http://arxiv.org/abs/2412.01145
Speculative decoding (SD) has been demonstrated as an effective technique for lossless LLM inference acceleration. Retrieval-based SD methods, one kind of model-free method, have yielded promising speedup, but they often rely on incomplete retrieval
Externí odkaz:
http://arxiv.org/abs/2411.10666
Autor:
Chen, Xiaodong, Hu, Yuxuan, Zhang, Xiaokang, Wang, Yanling, Li, Cuiping, Chen, Hong, Zhang, Jing
Pruning has become a widely adopted technique for reducing the hardware requirements of large language models (LLMs). To recover model performance after pruning, post-training is commonly employed to mitigate the resulting performance degradation. Wh
Externí odkaz:
http://arxiv.org/abs/2411.10272
With the rapid development of deep learning methods, there have been many breakthroughs in the field of text classification. Models developed for this task have been shown to achieve high accuracy. However, most of these models are trained using labe
Externí odkaz:
http://arxiv.org/abs/2409.13787
Autor:
Hu, Yuxuan, Tan, Minghuan, Zhang, Chenwei, Li, Zixuan, Liang, Xiaodan, Yang, Min, Li, Chengming, Hu, Xiping
Empathetic response generation is designed to comprehend the emotions of others and select the most appropriate strategies to assist them in resolving emotional challenges. Empathy can be categorized into cognitive empathy and affective empathy. The
Externí odkaz:
http://arxiv.org/abs/2407.21048
While preference-based recommendation algorithms effectively enhance user engagement by recommending personalized content, they often result in the creation of ``filter bubbles''. These bubbles restrict the range of information users interact with, i
Externí odkaz:
http://arxiv.org/abs/2404.04906
This paper introduces LLM-Streamline, a pioneer work on layer pruning for large language models (LLMs). It is based on the observation that different layers have varying impacts on hidden states, enabling the identification of less important layers t
Externí odkaz:
http://arxiv.org/abs/2403.19135
Despite significant recent progress in the field of autonomous driving, modern methods still struggle and can incur serious accidents when encountering long-tail unforeseen events and challenging urban scenarios. On the one hand, large language model
Externí odkaz:
http://arxiv.org/abs/2312.07488