Hugging Face Trending Papers July 2, 2026

Pmeta-TLA: Backdoor Attacks for Speech Classification Models via Meta-Learning with Timbre Leakage Attack

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Recently, speech classification methods have gained widespread adoption in intelligent gadgets. Current study indicates that backdoor attacks provide a substantial security concern to these models, underscoring the pressing necessity to investigate additional potential attack techniques to expose and prevent such risks.

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arXiv AI

Jul 3

Pmeta-TLA: Backdoor Attacks for Speech Classification Models via Meta-Learning with Timbre Leakage Attack

arXiv:2607. 01702v1 Announce Type: cross Abstract: Recently, speech classification methods have gained widespread adoption in intelligent gadgets.

By Yueming Huang, Wenhan Yao, Fen Xiao, Xiarun Chen, Weiping Wen

rag

arXiv Machine Learning

Jul 20

Natural Backdoor Attacks on Speech Recognition Models

arXiv:2607. 15724v1 Announce Type: cross Abstract: With the rapid development of deep learning, its vulnerability has gradually emerged in recent years.

By Jinwen Xin, Xixiang Lyu, Jing Ma

multimodal

arXiv Machine Learning

Jul 20

SpeechGuard: Online Defense against Backdoor Attacks on Speech Recognition Models

arXiv:2607. 15697v1 Announce Type: cross Abstract: Backdoor attacks pose a critical threat to neural network models, allowing attackers to implant a backdoor during the training phase by manipulating a small portion of the training data.

By Jinwen Xin, Xixiang Lv

agents robotics multimodal

arXiv AI

Jul 3

DRL-CLBA: A Clean Label Backdoor Attack for Speech Classification via DDPG Reinforcement Learning

arXiv:2607. 01729v1 Announce Type: new Abstract: Deep learning models for speech classification are vulnerable to backdoor attacks, where malicious triggers cause misclassification at inference time.

By Yueming Huang, Wenhan Yao, Fen Xiao, Xiarun Chen, Weiping Wen

diffusion reinforcement-learning fine-tuning efficiency

arXiv AI

Jun 6

Beyond Waveform Robustness: Robust Feature-Vocoder Adversarial Attacks on Automatic Speech Recognition

arXiv:2606. 05678v1 Announce Type: cross Abstract: Automatic speech recognition (ASR) systems have become widely used for multilingual speech-to-text transcription.

By Yifan Liao, Zongmin Zhang, Zhen Sun, Yuhui Sun, Xinhu Zheng, Xinlei He

multimodal benchmarks safety

arXiv Machine Learning

Jul 21

Precision-Varying Prediction (PVP): Robustifying ASR systems against adversarial attacks

arXiv:2603. 22590v2 Announce Type: replace Abstract: With the increasing deployment of automated and agentic systems, ensuring the adversarial robustness of automatic speech recognition (ASR) models has become highly relevant.

By Mat\'ias Pizarro, Raghavan Narasimhan, Jonas Killian, Asja Fischer

agents multimodal safety

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Pmeta-TLA: Backdoor Attacks for Speech Classification Models via Meta-Learning with Timbre Leakage Attack

Natural Backdoor Attacks on Speech Recognition Models

SpeechGuard: Online Defense against Backdoor Attacks on Speech Recognition Models

DRL-CLBA: A Clean Label Backdoor Attack for Speech Classification via DDPG Reinforcement Learning

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