Zobrazeno 1 - 10
of 2 798
pro vyhledávání: '"Cao, Meng"'
Autor:
Cao, Meng, Liu, Yuyang, Liu, Yingfei, Wang, Tiancai, Dong, Jiahua, Ding, Henghui, Zhang, Xiangyu, Reid, Ian, Liang, Xiaodan
Instruction tuning constitutes a prevalent technique for tailoring Large Vision Language Models (LVLMs) to meet individual task requirements. To date, most of the existing approaches are confined to single-task adaptation, whereas the requirements in
Externí odkaz:
http://arxiv.org/abs/2411.02564
Autor:
Mou, Shancong, Vemulapalli, Raviteja, Li, Shiyu, Liu, Yuxuan, Thomas, C, Cao, Meng, Bai, Haoping, Tuzel, Oncel, Huang, Ping, Shan, Jiulong, Shi, Jianjun
Defect segmentation is crucial for quality control in advanced manufacturing, yet data scarcity poses challenges for state-of-the-art supervised deep learning. Synthetic defect data generation is a popular approach for mitigating data challenges. How
Externí odkaz:
http://arxiv.org/abs/2410.18490
Autor:
Dong, Jiahua, Liang, Wenqi, Li, Hongliu, Zhang, Duzhen, Cao, Meng, Ding, Henghui, Khan, Salman, Khan, Fahad Shahbaz
Custom diffusion models (CDMs) have attracted widespread attention due to their astonishing generative ability for personalized concepts. However, most existing CDMs unreasonably assume that personalized concepts are fixed and cannot change over time
Externí odkaz:
http://arxiv.org/abs/2410.17594
As multimodal large language models (MLLMs) continue to demonstrate increasingly competitive performance across a broad spectrum of tasks, more intricate and comprehensive benchmarks have been developed to assess these cutting-edge models. These benc
Externí odkaz:
http://arxiv.org/abs/2410.06555
Autor:
Liu, Aiwei, Bai, Haoping, Lu, Zhiyun, Sun, Yanchao, Kong, Xiang, Wang, Simon, Shan, Jiulong, Jose, Albin Madappally, Liu, Xiaojiang, Wen, Lijie, Yu, Philip S., Cao, Meng
Direct Preference Optimization (DPO) has been widely adopted for preference alignment of Large Language Models (LLMs) due to its simplicity and effectiveness. However, DPO is derived as a bandit problem in which the whole response is treated as a sin
Externí odkaz:
http://arxiv.org/abs/2410.04350
Autor:
Chen, Hong-You, Lai, Zhengfeng, Zhang, Haotian, Wang, Xinze, Eichner, Marcin, You, Keen, Cao, Meng, Zhang, Bowen, Yang, Yinfei, Gan, Zhe
Contrastive Language-Image Pre-training (CLIP) has been a celebrated method for training vision encoders to generate image/text representations facilitating various applications. Recently, CLIP has been widely adopted as the vision backbone of multim
Externí odkaz:
http://arxiv.org/abs/2410.02746
Autor:
Lai, Zhengfeng, Saveris, Vasileios, Chen, Chen, Chen, Hong-You, Zhang, Haotian, Zhang, Bowen, Tebar, Juan Lao, Hu, Wenze, Gan, Zhe, Grasch, Peter, Cao, Meng, Yang, Yinfei
Recent advancements in multimodal models highlight the value of rewritten captions for improving performance, yet key challenges remain. For example, while synthetic captions often provide superior quality and image-text alignment, it is not clear wh
Externí odkaz:
http://arxiv.org/abs/2410.02740
Autor:
Zhang, Liang, Lin, Jionghao, Sabatini, John, Borchers, Conrad, Weitekamp, Daniel, Cao, Meng, Hollander, John, Hu, Xiangen, Graesser, Arthur C.
Learning performance data describe correct and incorrect answers or problem-solving attempts in adaptive learning, such as in intelligent tutoring systems (ITSs). Learning performance data tend to be highly sparse (80\%\(\sim\)90\% missing observatio
Externí odkaz:
http://arxiv.org/abs/2409.15631
Text-Video Retrieval (TVR) aims to align and associate relevant video content with corresponding natural language queries. Most existing TVR methods are based on large-scale pre-trained vision-language models (e.g., CLIP). However, due to the inheren
Externí odkaz:
http://arxiv.org/abs/2408.10575
Publikováno v:
APL Photonics 9, 086113 (2024)
$\pi$ modes are unique topological edge states appearing in Floquet systems with periodic modulations of the underlying lattice structure in evolution variable, such as dynamically modulated Su-Schrieffer-Heeger (SSH) lattices. These edge states are
Externí odkaz:
http://arxiv.org/abs/2408.07323