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20182026
most citedRelation Modeling with Graph Convolutional Networks for Facial Action Unit Detection

87 citations · 224 across the 60 of their papers we have counts for

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12 papers · 1 filter

eess.AS2026

AD-Mamba: Architecture-Complementary Knowledge Distillation for Efficient and Robust Audio Classification

Junyu Wang, Tianrui Wang, Meng Ge +3

Recent advancements in large-scale audio classification have been primarily driven by Transformer-based architectures due to their strong capacity in modeling long-range dependenci…

cs.CL2026

LLM-Anchored Paralinguistic Enrichment for Alzheimer's Disease Detection

Xiao Wei, Yuqin Lin, Yaru Cao +6

Speech-based automatic detection of Alzheimer's disease (AD) provides a non-invasive and scalable approach to early cognitive screening. AD affects both lexical-semantic organizati…

cs.CL2026

EmoS: A Theory-Grounded Framework for Evaluating and Aligning Emotional Intelligence in Spoken Language Models

Junyu Wang, Siyuan Zhang, Peiyuan Jiang +11

Despite significant advances in instruction-following and auditory comprehension, the evaluation of Emotional Intelligence (EI) in Spoken Language Models (SLMs) remains confined to…

cs.CL2026

Gated Multi-Graph Fusion via Graph Attention Networks for Alzheimer's Disease Detection

Jinyu Li, Xiao Wei, Bin Wen +5

Spontaneous speech is a vital non-invasive biomarker for Alzheimer's Disease (AD), yet many systems overlook non-linear structural disruptions and clinical heterogeneity in patholo…

eess.AS2026

EChO-Agent: Evidence Chain Orchestration Agent for Audio Reasoning

Siyuan Zhang, Jian Zong, Junyu Wang +7

While LALMs show promise on audio question answering, they fail to focus on question-relevant segments of audio and provide a clear, checkable reasoning process when dealing with c…

cs.SD2026

Speech Meets ELF: Audio Conditional Continuous-Target Diffusion for Speech Recognition and Translation

Xuanchen Li, Tianrui Wang, Yuheng Lu +11

Speech-to-text (S2T) systems for recognition (ASR) and translation (S2TT) typically generate discrete text tokens. In contrast, continuous-target language modelling performs genera…

cs.CL2026

CECOR: Correction-oriented synthetic data construction for factual error correction

Lei Zhu, Xiaobao Wang, Jianbiao Yang +4

Factual Error Correction (FEC) aims to revise inaccurate text into statements that are factually consistent with external evidence. Although recent methods perform well on single-h…

cs.AI2026

Separate First, Fuse Later: Mitigating Cross-Modal Interference in Audio-Visual LLMs Reasoning with Modality-Specific Chain-of-Thought

Xuanchen Li, Yuheng Lu, Chenrui Cui +6

Audio and vision provide complementary evidence for audio-visual question answering, yet current audio-visual large language models may suffer from cross-modal interference: inform…

eess.AS2026

Evaluating the Expressive Appropriateness of Speech in Rich Contexts

Tianrui Wang, Ziyang Ma, Yizhou Peng +26

Evaluating expressive speech remains challenging, as existing methods mainly assess emotional intensity and overlook whether a speech sample is expressively appropriate for its con…

eess.AS2026

UniSonate: A Unified Model for Speech, Music, and Sound Effect Generation with Text Instructions

Chunyu Qiang, Xiaopeng Wang, Kang Yin +11

Generative audio modeling has largely been fragmented into specialized tasks, text-to-speech (TTS), text-to-music (TTM), and text-to-audio (TTA), each operating under heterogeneous…

cs.SD2026

MSR-HuBERT: Self-supervised Pre-training for Adaptation to Multiple Sampling Rates

Zikang Huang, Meng Ge, Tianrui Wang +4

Self-supervised learning (SSL) has advanced speech processing. However, existing speech SSL methods typically assume a single sampling rate and struggle with mixed-rate data due to…

cs.CL2026

Breaking Data Efficiency Dilemma: A Federated and Augmented Learning Framework For Alzheimer's Disease Detection via Speech

Xiao Wei, Bin Wen, Yuqin Lin +5

Early diagnosis of Alzheimer's Disease (AD) is crucial for delaying its progression. While AI-based speech detection is non-invasive and cost-effective, it faces a critical data ef…