2 citations · 3 across the 4 of their papers we have counts for
5 papers
Benchmarking Cross-Domain Audio-Visual Deception Detection
Xiaobao Guo, Zitong Yu, Nithish Muthuchamy Selvaraj +3
Automated deception detection is crucial for assisting humans in accurately assessing truthfulness and identifying deceptive behavior. Conventional contact-based techniques, like p…
Improving Concept Alignment in Vision-Language Concept Bottleneck Models
Nithish Muthuchamy Selvaraj, Xiaobao Guo, Adams Wai-Kin Kong +1
Concept Bottleneck Models (CBM) map images to human-interpretable concepts before making class predictions. Recent approaches automate CBM construction by prompting Large Language…
Audio-Visual Deception Detection: DOLOS Dataset and Parameter-Efficient Crossmodal Learning
Xiaobao Guo, Nithish Muthuchamy Selvaraj, Zitong Yu +3
Deception detection in conversations is a challenging yet important task, having pivotal applications in many fields such as credibility assessment in business, multimedia anti-fra…
Flexible-modal Deception Detection with Audio-Visual Adapter
Zhaoxu Li, Zitong Yu, Nithish Muthuchamy Selvaraj +4
Detecting deception by human behaviors is vital in many fields such as custom security and multimedia anti-fraud. Recently, audio-visual deception detection attracts more attention…
Adapter Incremental Continual Learning of Efficient Audio Spectrogram Transformers
Nithish Muthuchamy Selvaraj, Xiaobao Guo, Adams Kong +2
Continual learning involves training neural networks incrementally for new tasks while retaining the knowledge of previous tasks. However, efficiently fine-tuning the model for seq…