1 citations · 1 across the 4 of their papers we have counts for
4 papers
Towards Effective Long Video Understanding of Multimodal Large Language Models via One-shot Clip Retrieval
Tao Chen, Shaobo Ju, Qiong Wu +6
Due to excessive memory overhead, most Multimodal Large Language Models (MLLMs) can only process videos of limited frames. In this paper, we propose an effective and efficient para…
SUMMA: A Multimodal Large Language Model for Advertisement Summarization
Weitao Jia, Shuo Yin, Zhoufutu Wen +6
Understanding multimodal video ads is crucial for improving query-ad matching and relevance ranking on short video platforms, enhancing advertising effectiveness and user experienc…
Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directions
Kun Zhang, Le Wu, Kui Yu +2
Large Language Models (LLMs) have gained enormous attention in recent years due to their capability of understanding and generating natural languages. With the rapid development an…
Reducing Hyperparameter Tuning Costs in ML, Vision and Language Model Training Pipelines via Memoization-Awareness
Abdelmajid Essofi, Ridwan Salahuddeen, Munachiso Nwadike +5
The training or fine-tuning of machine learning, vision, and language models is often implemented as a pipeline: a sequence of stages encompassing data preparation, model training…