3 citations · 8 across the 12 of their papers we have counts for
12 papers
Out-of-Distribution Detection Based on Total Variation Estimation
Dabiao Ma, Zhiba Su, Jian Yang +1
This paper introduces a novel approach to securing machine learning model deployments against potential distribution shifts in practical applications, the Total Variation Out-of-Di…
NSR-Boost: A Neuro-Symbolic Residual Boosting Framework for Industrial Legacy Models
Ziming Dai, Dabiao Ma, Jinle Tong +5
Although the Gradient Boosted Decision Trees (GBDTs) dominate industrial tabular applications, upgrading legacy models in high-concurrency production environments still faces prohi…
TS-PEFT: Unveiling Token-Level Redundancy in Parameter-Efficient Fine-Tuning
Dabiao Ma, Ziming Dai, Zhimin Xin +3
Current Parameter-Efficient Fine-Tuning (PEFT) methods typically operate under an implicit assumption: Once a target module is selected, every token passing through it contributes…
QvTAD: Differential Relative Attribute Learning for Voice Timbre Attribute Detection
Zhiyu Wu, Jingyi Fang, Yufei Tang +3
Voice Timbre Attribute Detection (vTAD) plays a pivotal role in fine-grained timbre modeling for speech generation tasks. However, it remains challenging due to the inherently subj…
SpecWav-Attack: Leveraging Spectrogram Resizing and Wav2Vec 2.0 for Attacking Anonymized Speech
Yuqi Li, Yuanzhong Zheng, Zhongtian Guo +3
This paper presents SpecWav-Attack, an adversarial model for detecting speakers in anonymized speech. It leverages Wav2Vec2 for feature extraction and incorporates spectrogram resi…
Qieemo: Speech Is All You Need in the Emotion Recognition in Conversations
Jinming Chen, Jingyi Fang, Yuanzhong Zheng +2
Emotion recognition plays a pivotal role in intelligent human-machine interaction systems. Multimodal approaches benefit from the fusion of diverse modalities, thereby improving th…
SFE-Net: Harnessing Biological Principles of Differential Gene Expression for Improved Feature Selection in Deep Learning Networks
Yuqi Li, Yuanzhong Zheng, Yaoxuan Wang +2
In the realm of DeepFake detection, the challenge of adapting to various synthesis methodologies such as Faceswap, Deepfakes, Face2Face, and NeuralTextures significantly impacts th…
Leveraging MLLM Embeddings and Attribute Smoothing for Compositional Zero-Shot Learning
Xudong Yan, Songhe Feng, Yang Zhang +3
Compositional zero-shot learning (CZSL) aims to recognize novel compositions of attributes and objects learned from seen compositions. Previous works disentangle attributes and obj…
Qifusion-Net: Layer-adapted Stream/Non-stream Model for End-to-End Multi-Accent Speech Recognition
Jinming Chen, Jingyi Fang, Yuanzhong Zheng +2
Currently, end-to-end (E2E) speech recognition methods have achieved promising performance. However, auto speech recognition (ASR) models still face challenges in recognizing multi…
Ms-senet: Enhancing Speech Emotion Recognition Through Multi-scale Feature Fusion With Squeeze-and-excitation Blocks
Mengbo Li, Yuanzhong Zheng, Dichucheng Li +3
Speech Emotion Recognition (SER) has become a growing focus of research in human-computer interaction. Spatiotemporal features play a crucial role in SER, yet current research lack…
Mao-Zedong At SemEval-2023 Task 4: Label Represention Multi-Head Attention Model With Contrastive Learning-Enhanced Nearest Neighbor Mechanism For Multi-Label Text Classification
Che Zhang, Ping'an Liu, Zhenyang Xiao +1
The study of human values is essential in both practical and theoretical domains. With the development of computational linguistics, the creation of large-scale datasets has made i…
AmGCL: Feature Imputation of Attribute Missing Graph via Self-supervised Contrastive Learning
Xiaochuan Zhang, Mengran Li, Ye Wang +1
Attribute graphs are ubiquitous in multimedia applications, and graph representation learning (GRL) has been successful in analyzing attribute graph data. However, incomplete graph…