46 citations · 74 across the 23 of their papers we have counts for
4 papers · 1 filter
VideoLatent: Video-Language Learning via Latent Self-Forcing
Zi-Yuan Hu, Zicong Tang, Shijia Huang +3
Recent advancements in chain-of-thought (CoT) reasoning have shown promise in enhancing video understanding and reasoning capabilities of multimodal large language models (MLLMs).…
NeMo: Needle in a Montage for Video-Language Understanding
Zi-Yuan Hu, Shuo Liang, Duo Zheng +10
Recent advances in video large language models (VideoLLMs) call for new evaluation protocols and benchmarks for video-language understanding. Inspired by the needle in a haystack t…
Learning from Videos for 3D World: Enhancing MLLMs with 3D Vision Geometry Priors
Duo Zheng, Shijia Huang, Yanyang Li +1
Previous research has investigated the application of Multimodal Large Language Models (MLLMs) in understanding 3D scenes by interpreting them as videos. These approaches generally…
VL-PET: Vision-and-Language Parameter-Efficient Tuning via Granularity Control
Zi-Yuan Hu, Yanyang Li, Michael R. Lyu +1
As the model size of pre-trained language models (PLMs) grows rapidly, full fine-tuning becomes prohibitively expensive for model training and storage. In vision-and-language (VL),…