1 citations · 3 across the 4 of their papers we have counts for
4 papers
SOVA-Bench: Benchmarking the Speech Conversation Ability for LLM-based Voice Assistant
Yixuan Hou, Heyang Liu, Yuhao Wang +5
Thanks to the steady progress of large language models (LLMs), speech encoding algorithms and vocoder structure, recent advancements have enabled generating speech response directl…
VocalNet: Speech LLM with Multi-Token Prediction for Faster and High-Quality Generation
Yuhao Wang, Heyang Liu, Ziyang Cheng +4
Speech large language models (LLMs) have emerged as a prominent research focus in speech processing. We introduce VocalNet-1B and VocalNet-8B, a series of high-performance, low-lat…
S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression
Yunuo Chen, Qian Li, Bing He +6
Transformer-based Learned Image Compression (LIC) suffers from a suboptimal trade-off between decoding latency and rate-distortion (R-D) performance. Moreover, the critical role of…
Linear Attention Modeling for Learned Image Compression
Donghui Feng, Zhengxue Cheng, Shen Wang +4
Recent years, learned image compression has made tremendous progress to achieve impressive coding efficiency. Its coding gain mainly comes from non-linear neural network-based tran…