Youngjoon Jang
Orcid: 0009-0002-0500-6025Affiliations:
- Korea Advanced Institute of Science and Technology (KAIST), Multimodal AI Lab, Daejeon, South Korea
According to our database1,
Youngjoon Jang
authored at least 18 papers
between 2022 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
EDNet: A Distortion-Agnostic Speech Enhancement Framework with Gating Mamba Mechanism and Phase Shift-Invariant Training.
CoRR, June, 2025
Fork-Merge Decoding: Enhancing Multimodal Understanding in Audio-Visual Large Language Models.
CoRR, May, 2025
AVCD: Mitigating Hallucinations in Audio-Visual Large Language Models through Contrastive Decoding.
CoRR, May, 2025
CoRR, March, 2025
VoiceDiT: Dual-Condition Diffusion Transformer for Environment-Aware Speech Synthesis.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025
Lost in Translation, Found in Context: Sign Language Translation with Contextual Cues.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025
2024
Let Me Finish My Sentence: Video Temporal Grounding with Holistic Text Understanding.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024
Proceedings of the IEEE International Conference on Acoustics, 2024
Seeing Through The Conversation: Audio-Visual Speech Separation Based on Diffusion Model.
Proceedings of the IEEE International Conference on Acoustics, 2024
Proceedings of the IEEE International Conference on Acoustics, 2024
Proceedings of the IEEE International Conference on Acoustics, 2024
Proceedings of the IEEE International Conference on Acoustics, 2024
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
2023
Proceedings of the 31st ACM International Conference on Multimedia, 2023
Proceedings of the IEEE International Conference on Acoustics, 2023
Proceedings of the IEEE International Conference on Acoustics, 2023
2022
Signing Outside the Studio: Benchmarking Background Robustness for Continuous Sign Language Recognition.
Proceedings of the 33rd British Machine Vision Conference 2022, 2022