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20242026
most citedvideo-SALMONN-o1: Reasoning-enhanced Audio-visual Large Language Model

2 citations · 5 across the 17 of their papers we have counts for

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cs.SD2026

Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection

Hangbin Yu, Yudong Yang, Rongfeng Su +2

Automatic depression detection using speech signals with acoustic and textual modalities is a promising approach for early diagnosis. Depression-related patterns exhibit sparsity i…

cs.SD2026

From Speech to Profile: A Protocol-Driven LLM Agent for Psychological Profile Generation

Xingjian Yang, Yudong Yang, Zhixing Guo +3

The psychological profile that structurally documents the case of a depression patient is essential for psychotherapy. Large language models can be applied to summarize the profile…

cs.SD2025

Speech-Audio Compositional Attacks on Multimodal LLMs and Their Mitigation with SALMONN-Guard

Yudong Yang, Xuezhen Zhang, Zhifeng Han +6

Recent progress in LLMs has enabled understanding of audio signals, but has also exposed new safety risks arising from complex audio inputs that are inadequately handled by current…

cs.SD2025

UTI-LLM: A Personalized Articulatory-Speech Therapy Assistance System Based on Multimodal Large Language Model

Yudong Yang, Xiaokang Liu, Shaofeng zhao +3

Speech therapy is essential for rehabilitating speech disorders caused by neurological impairments such as stroke. However, traditional manual and computer-assisted systems are lim…

cs.SD20241 cited

An Audio-textual Diffusion Model For Converting Speech Signals Into Ultrasound Tongue Imaging Data

Yudong Yang, Rongfeng Su, Xiaokang Liu +2

Acoustic-to-articulatory inversion (AAI) is to convert audio into articulator movements, such as ultrasound tongue imaging (UTI) data. An issue of existing AAI methods is only usin…