Zobrazeno 1 - 10
of 26 003
pro vyhledávání: '"A. Dehghan"'
Autor:
Zhang, Haotian, Gao, Mingfei, Gan, Zhe, Dufter, Philipp, Wenzel, Nina, Huang, Forrest, Shah, Dhruti, Du, Xianzhi, Zhang, Bowen, Li, Yanghao, Dodge, Sam, You, Keen, Yang, Zhen, Timofeev, Aleksei, Xu, Mingze, Chen, Hong-You, Fauconnier, Jean-Philippe, Lai, Zhengfeng, You, Haoxuan, Wang, Zirui, Dehghan, Afshin, Grasch, Peter, Yang, Yinfei
We present MM1.5, a new family of multimodal large language models (MLLMs) designed to enhance capabilities in text-rich image understanding, visual referring and grounding, and multi-image reasoning. Building upon the MM1 architecture, MM1.5 adopts
Externí odkaz:
http://arxiv.org/abs/2409.20566
[Context] Large Language Models (LLMs) have shown good performance in several software development-related tasks such as program repair, documentation, code refactoring, debugging, and testing. Adapters are specialized, small modules designed for par
Externí odkaz:
http://arxiv.org/abs/2408.09568
Autor:
Karakaya, Erciyes, Ercetin, Ozgur, Ozkan, Huseyin, Karaca, Mehmet, Biyar, Elham Dehghan, Palaios, Alexandros
The growing complexity of networks and the variety of future scenarios with diverse and often stringent performance requirements call for a higher level of automation. Intent-based management emerges as a solution to attain high level of automation,
Externí odkaz:
http://arxiv.org/abs/2407.17767
Autor:
Xu, Mingze, Gao, Mingfei, Gan, Zhe, Chen, Hong-You, Lai, Zhengfeng, Gang, Haiming, Kang, Kai, Dehghan, Afshin
We propose SlowFast-LLaVA (or SF-LLaVA for short), a training-free video large language model (LLM) that can jointly capture detailed spatial semantics and long-range temporal context without exceeding the token budget of commonly used LLMs. This is
Externí odkaz:
http://arxiv.org/abs/2407.15841
Autor:
Bruns, Axel, Kasianenko, Kateryna, Suresh, Vishnu Padinjaredath, Dehghan, Ehsan, Vodden, Laura
This article introduces the analytical approach of practice mapping, using vector embeddings of network actions and interactions to map commonalities and disjunctures in the practices of social media users, as a framework for methodological advanceme
Externí odkaz:
http://arxiv.org/abs/2407.05956
Autor:
Amirloo, Elmira, Fauconnier, Jean-Philippe, Roesmann, Christoph, Kerl, Christian, Boney, Rinu, Qian, Yusu, Wang, Zirui, Dehghan, Afshin, Yang, Yinfei, Gan, Zhe, Grasch, Peter
Preference alignment has become a crucial component in enhancing the performance of Large Language Models (LLMs), yet its impact in Multimodal Large Language Models (MLLMs) remains comparatively underexplored. Similar to language models, MLLMs for im
Externí odkaz:
http://arxiv.org/abs/2407.02477
Autor:
Dehghan, Mohammad, Alomrani, Mohammad Ali, Bagga, Sunyam, Alfonso-Hermelo, David, Bibi, Khalil, Ghaddar, Abbas, Zhang, Yingxue, Li, Xiaoguang, Hao, Jianye, Liu, Qun, Lin, Jimmy, Chen, Boxing, Parthasarathi, Prasanna, Biparva, Mahdi, Rezagholizadeh, Mehdi
The emerging citation-based QA systems are gaining more attention especially in generative AI search applications. The importance of extracted knowledge provided to these systems is vital from both accuracy (completeness of information) and efficienc
Externí odkaz:
http://arxiv.org/abs/2406.10393
Autor:
Bachmann, Roman, Kar, Oğuzhan Fatih, Mizrahi, David, Garjani, Ali, Gao, Mingfei, Griffiths, David, Hu, Jiaming, Dehghan, Afshin, Zamir, Amir
Current multimodal and multitask foundation models like 4M or UnifiedIO show promising results, but in practice their out-of-the-box abilities to accept diverse inputs and perform diverse tasks are limited by the (usually rather small) number of moda
Externí odkaz:
http://arxiv.org/abs/2406.09406
Recently, frame multipliers, pair frames, and controlled frames have been investigated to improve the numerical efficiency of iterative algorithms for inverting the frame operator and other applications of frames. In this paper, the concept of bifram
Externí odkaz:
http://arxiv.org/abs/2405.16990
Publikováno v:
New Microbes and New Infections, Vol 44, Iss , Pp 100943- (2021)
Stenotrophomonas maltophilia has emerged as an important nosocomial pathogen. Treatment of S. maltophilia infections is difficult due to increasing resistance to multiple antibacterial agents. In this 12-month cross-sectional study, from 2017 to 2018
Externí odkaz:
https://doaj.org/article/c961925c311c451e8d41fff806d23175