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Song Yang

7 accepted papers

2025

Large Language Model Meets Graph Neural Network in Knowledge Distillation

AAAI 2025technical

While Large Language Models (LLMs) show promise for Text-Attributed Graphs (TAGs) learning, their deployment is hindered by computational demands. Graph Neural Networks (GNNs) are efficient but struggle with TAGs' complex semantics. We propose LinguGKD, a novel LLM-to-GNN knowledge distillation fram…

Cited by 5SourcePDFScholar
2023

USER: Unsupervised Structural Entropy-Based Robust Graph Neural Network

AAAI 2023technical

Unsupervised/self-supervised graph neural networks (GNN) are susceptible to the inherent randomness in the input graph data, which adversely affects the model's performance in downstream tasks. In this paper, we propose USER, an unsupervised and robust version of GNN based on structural entropy, to…

2022

Channel-Wise AV-Fusion Attention for Multi-Channel Audio-Visual Speech Recognition

ICASSP 2022accepted

In this paper, we present our work for automatic speech recognition (ASR) in the Multimodal Information Based Speech Processing (MISP) Challenge 2021. We proposed a combination of the guided source separation-based (GSS) speech enhancement technique and a novel Channel-wise Av-fusion encoder (CAE) b…

Cited by 0SourceScholar
2022

Rethinking the Video Sampling and Reasoning Strategies for Temporal Sentence Grounding

EMNLP 2022finding

Temporal sentence grounding (TSG) aims to identify the temporal boundary of a specific segment from an untrimmed video by a sentence query. All existing works first utilize a sparse sampling strategy to extract a fixed number of video frames and then interact them with query for reasoning.However, w…

Cited by 22SourcePDFScholar
2020

Multimodal Learning for Classroom Activity Detection

ICASSP 2020accepted

Classroom activity detection (CAD) focuses on accurately classifying whether the teacher or student is speaking and recording both the length of individual utterances during a class. A CAD solution helps teachers get instant feedback on their pedagogical instructions. This greatly improves educators…

Cited by 0SourceScholar