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20242026
most citedA Contemporary Overview: Trends and Applications of Large Language Models on Mobile Devices

1 citations · 4 across the 15 of their papers we have counts for

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cs.AI2024★ 1 cited

A Contemporary Overview: Trends and Applications of Large Language Models on Mobile Devices

Lianjun Liu, Hongli An, Pengxuan Chen +1

With the rapid development of large language models (LLMs), which possess powerful natural language processing and generation capabilities, LLMs are poised to provide more natural…

cs.SD2024

Does Current Deepfake Audio Detection Model Effectively Detect ALM-based Deepfake Audio?

Yuankun Xie, Chenxu Xiong, Xiaopeng Wang +9

Currently, Audio Language Models (ALMs) are rapidly advancing due to the developments in large language models and audio neural codecs. These ALMs have significantly lowered the ba…

cs.SD2024

Temporal Variability and Multi-Viewed Self-Supervised Representations to Tackle the ASVspoof5 Deepfake Challenge

Yuankun Xie, Xiaopeng Wang, Zhiyong Wang +4

ASVspoof5, the fifth edition of the ASVspoof series, is one of the largest global audio security challenges. It aims to advance the development of countermeasure (CM) to discrimina…

cs.SD2024★ 1 cited

Generalized Source Tracing: Detecting Novel Audio Deepfake Algorithm with Real Emphasis and Fake Dispersion Strategy

Yuankun Xie, Ruibo Fu, Zhengqi Wen +5

With the proliferation of deepfake audio, there is an urgent need to investigate their attribution. Current source tracing methods can effectively distinguish in-distribution (ID)…

cs.SD2024★ 1 cited

The Codecfake Dataset and Countermeasures for the Universally Detection of Deepfake Audio

Yuankun Xie, Yi Lu, Ruibo Fu +9

With the proliferation of Audio Language Model (ALM) based deepfake audio, there is an urgent need for generalized detection methods. ALM-based deepfake audio currently exhibits wi…