Search Results for author:
Found 4 papers, 2 papers with code
HyperLLaVA: Dynamic Visual and Language Expert Tuning for Multimodal Large Language Models
Recent advancements indicate that scaling up Multimodal Large Language Models (MLLMs) effectively enhances performance on downstream multimodal tasks.
Ranked #76 on
Visual Question Answering
on MM-Vet
Compress & Align: Curating Image-Text Data with Human Knowledge
The massive growth of image-text data through web crawling inherently presents the challenge of variability in data quality.
Audio-Visual LLM for Video Understanding
This paper presents Audio-Visual LLM, a Multimodal Large Language Model that takes both visual and auditory inputs for holistic video understanding.
Masked Contrastive Pre-Training for Efficient Video-Text Retrieval
Our MAC aims to reduce video representation's spatial and temporal redundancy in the VidLP model by a mask sampling mechanism to improve pre-training efficiency.
Ranked #37 on
Video Retrieval
on MSR-VTT-1kA
(using extra training data)
