fine-tuning 1large language models 1risk detection 1safety assessment 1semantic analysis 1subspace alignment 1
From the 1 of 2 linked papers with an AI index.
2 papers
eess.AS2026
Qwen-Audio-3.0-TTS: Freely Controllable and Highly Robust Speech Synthesis with Multi-Stage Training Paradigm
Bajian Xiang, Cheng Wen, Han Zhao +12
In this report, we present Qwen-Audio-3.0-TTS, a production-oriented speech synthesis system that jointly advances content consistency, speaker similarity, prosodic naturalness, au…
cs.CR2026
DataShield: Uncovering Risky Fine-Tuning Data Across LLMs Through Consensus Subspace Alignment
Zefeng Wu, Weiwei Qi, Jielong Chen +6
The paper introduces DataShield, a framework that detects risky fine‑tuning data for large language models by aligning safety‑critical semantic subspaces across multiple safety‑ali…