11 citations · 29 across the 9 of their papers we have counts for
9 papers
DenoiseRotator: Enhance Pruning Robustness for LLMs via Importance Concentration
Tianteng Gu, Bei Liu, Bo Xiao +3
Pruning is a widely used technique to compress large language models (LLMs) by removing unimportant weights, but it often suffers from significant performance degradation - especia…
Memory-Efficient Training for Deep Speaker Embedding Learning in Speaker Verification
Bei Liu, Yanmin Qian
Recent speaker verification (SV) systems have shown a trend toward adopting deeper speaker embedding extractors. Although deeper and larger neural networks can significantly improv…
Towards Lightweight Speaker Verification via Adaptive Neural Network Quantization
Bei Liu, Haoyu Wang, Yanmin Qian
Modern speaker verification (SV) systems typically demand expensive storage and computing resources, thereby hindering their deployment on mobile devices. In this paper, we explore…
CLAQ: Pushing the Limits of Low-Bit Post-Training Quantization for LLMs
Haoyu Wang, Bei Liu, Hang Shao +4
Parameter quantization for Large Language Models (LLMs) has attracted increasing attentions recently in reducing memory costs and improving computational efficiency. Early approach…
One-Shot Sensitivity-Aware Mixed Sparsity Pruning for Large Language Models
Hang Shao, Bei Liu, Bo Xiao +3
Various Large Language Models~(LLMs) from the Generative Pretrained Transformer(GPT) family have achieved outstanding performances in a wide range of text generation tasks. However…
DQ-Whisper: Joint Distillation and Quantization for Efficient Multilingual Speech Recognition
Hang Shao, Bei Liu, Wei Wang +2
As a popular multilingual and multitask pre-trained speech model, Whisper has the problem of curse of multilinguality. To enhance multilingual capabilities in small Whisper models,…
Build a SRE Challenge System: Lessons from VoxSRC 2022 and CNSRC 2022
Zhengyang Chen, Bing Han, Xu Xiang +3
Many speaker recognition challenges have been held to assess the speaker verification system in the wild and probe the performance limit. Voxceleb Speaker Recognition Challenge (Vo…
SJTU-AISPEECH System for VoxCeleb Speaker Recognition Challenge 2022
Zhengyang Chen, Bing Han, Xu Xiang +3
This report describes the SJTU-AISPEECH system for the Voxceleb Speaker Recognition Challenge 2022. For track1, we implemented two kinds of systems, the online system and the offli…
The SJTU X-LANCE Lab System for CNSRC 2022
Zhengyang Chen, Bei Liu, Bing Han +2
This technical report describes the SJTU X-LANCE Lab system for the three tracks in CNSRC 2022. In this challenge, we explored the speaker embedding modeling ability of deep ResNet…