271 citations · 294 across the 5 of their papers we have counts for
5 papers
X-LLM: Bootstrapping Advanced Large Language Models by Treating Multi-Modalities as Foreign Languages
Feilong Chen, Minglun Han, Haozhi Zhao +4
Large language models (LLMs) have demonstrated remarkable language abilities. GPT-4, based on advanced LLMs, exhibits extraordinary multimodal capabilities beyond previous visual l…
VILAS: Exploring the Effects of Vision and Language Context in Automatic Speech Recognition
Ziyi Ni, Minglun Han, Feilong Chen +4
Enhancing automatic speech recognition (ASR) performance by leveraging additional multimodal information has shown promising results in previous studies. However, most of these wor…
Knowledge Transfer from Pre-trained Language Models to Cif-based Speech Recognizers via Hierarchical Distillation
Minglun Han, Feilong Chen, Jing Shi +2
Large-scale pre-trained language models (PLMs) have shown great potential in natural language processing tasks. Leveraging the capabilities of PLMs to enhance automatic speech reco…
VLP: A Survey on Vision-Language Pre-training
Feilong Chen, Duzhen Zhang, Minglun Han +4
In the past few years, the emergence of pre-training models has brought uni-modal fields such as computer vision (CV) and natural language processing (NLP) to a new era. Substantia…
DMRM: A Dual-channel Multi-hop Reasoning Model for Visual Dialog
Feilong Chen, Fandong Meng, Jiaming Xu +3
Visual Dialog is a vision-language task that requires an AI agent to engage in a conversation with humans grounded in an image. It remains a challenging task since it requires the…