13 citations · 17 across the 13 of their papers we have counts for
18 papers
PocketTSLM: Deploying an On-Device Soft-Prompt Time-Series Language Model for Privacy-Preserving Smartphone Reasoning
Max Rosenblattl, Nikhil Krishnaswamy, Leon Nissen +9
Consumer phones and wearables increasingly collect physiological time-series data, yet most mobile systems treat these streams as summaries or text rather than as temporal evidence…
DeBERTa-ConPara: Attack-Aware and Deployment-Realistic Detection of AI-Generated Text
Mohamed Mady, Yupei Li, Johannes Reschke +1
Robust detection of AI-generated text under deployment conditions is challenging: distribution shifts across domains and generators, adversarial perturbations of the input surface,…
CLASH: Counterfactual Auditing of Lexical and Prosodic Reliance in Spoken Sarcasm Detection
Qiyang Sun, Xudong Li, Yupei Li +4
Spoken sarcasm detectors may exploit lexical content, prosody, or their interaction, yet conventional evaluation cannot reveal which cues drive their predictions. We introduce CLAS…
XAI-Grounded Explanation Generation for Speech Deepfake Detection with Training-Free Multimodal Large Language Models
Yupei Li, Qiyang Sun, Xiaoliang Wu +3
Speech deepfake detection (SDD) systems require trustworthy explanations for reliable decision-making. Existing explanation ways mainly fall into two categories. Traditional explai…
Enhancing Efficiency and Performance in Deepfake Audio Detection through Neuron-level Dropin & Neuroplasticity Mechanisms
Yupei Li, Shuaijie Shao, Manuel Milling +1
Current audio deepfake detection has achieved remarkable performance using diverse deep learning architectures such as ResNet, and has seen further improvements with the introducti…
Affect and Effect: Limitations of regularisation-based continual learning in EEG-based emotion classification
Nina Peire, Yupei Li, Björn Schuller
Generalisation to unseen subjects in EEG-based emotion classification remains a challenge due to high inter-and intra-subject variability. Continual learning (CL) poses a promising…
RAxSS: Retrieval-Augmented Sparse Sampling for Explainable Variable-Length Medical Time Series Classification
Aydin Javadov, Samir Garibov, Tobias Hoesli +4
Medical time series analysis is challenging due to data sparsity, noise, and highly variable recording lengths. Prior work has shown that stochastic sparse sampling effectively han…
Artificial Emotion: A Survey of Theories and Debates on Realising Emotion in Artificial Intelligence
Yupei Li, Qiyang Sun, Michelle Schlicher +2
Affective Computing (AC) has enabled Artificial Intelligence (AI) systems to recognise, interpret, and respond to human emotions - a capability also known as Artificial Emotional I…
Large Language Models for Depression Recognition in Spoken Language Integrating Psychological Knowledge
Yupei Li, Shuaijie Shao, Manuel Milling +1
Depression is a growing concern gaining attention in both public discourse and AI research. While deep neural networks (DNNs) have been used for recognition, they still lack real-w…
Neuroplasticity in Artificial Intelligence -- An Overview and Inspirations on Drop In & Out Learning
Yupei Li, Manuel Milling, Björn W. Schuller
Artificial Intelligence (AI) has achieved new levels of performance and spread in public usage with the rise of deep neural networks (DNNs). Initially inspired by human neurons and…
GatedxLSTM: A Multimodal Affective Computing Approach for Emotion Recognition in Conversations
Yupei Li, Qiyang Sun, Sunil Munthumoduku Krishna Murthy +2
Affective Computing (AC) is essential for advancing Artificial General Intelligence (AGI), with emotion recognition serving as a key component. However, human emotions are inherent…
DOTA-ME-CS: Daily Oriented Text Audio-Mandarin English-Code Switching Dataset
Yupei Li, Zifan Wei, Heng Yu +3
Code-switching, the alternation between two or more languages within communication, poses great challenges for Automatic Speech Recognition (ASR) systems. Existing models and datas…
Towards Friendly AI: A Comprehensive Review and New Perspectives on Human-AI Alignment
Qiyang Sun, Yupei Li, Emran Alturki +2
As Artificial Intelligence (AI) continues to advance rapidly, Friendly AI (FAI) has been proposed to advocate for more equitable and fair development of AI. Despite its importance,…
Explainable Detection of Machine Generated Music and Early Systematic Evaluation
Yupei Li, Qiyang Sun, Hanqian Li +2
Machine-generated music (MGM) has become a groundbreaking innovation with wide-ranging applications, such as music therapy, personalised editing, and creative inspiration within th…
Discourse Features Enhance Detection of Document-Level Machine-Generated Content
Yupei Li, Manuel Milling, Lucia Specia +1
The availability of high-quality APIs for Large Language Models (LLMs) has facilitated the widespread creation of Machine-Generated Content (MGC), posing challenges such as academi…
autrainer: A Modular and Extensible Deep Learning Toolkit for Computer Audition Tasks
Simon Rampp, Andreas Triantafyllopoulos, Manuel Milling +1
This work introduces the key operating principles for autrainer, our new deep learning training framework for computer audition tasks. autrainer is a PyTorch-based toolkit that all…
M6: Multi-generator, Multi-domain, Multi-lingual and cultural, Multi-genres, Multi-instrument Machine-Generated Music Detection Databases
Yupei Li, Hanqian Li, Lucia Specia +1
Machine-generated music (MGM) has emerged as a powerful tool with applications in music therapy, personalised editing, and creative inspiration for the music community. However, it…
From Audio Deepfake Detection to AI-Generated Music Detection -- A Pathway and Overview
Yupei Li, Manuel Milling, Lucia Specia +1
As Artificial Intelligence (AI) technologies continue to evolve, their use in generating realistic, contextually appropriate content has expanded into various domains. Music, an ar…