Zobrazeno 1 - 10
of 929
pro vyhledávání: '"Yanda, P"'
Autor:
Wu, Yanda, Profumo, Stefano
If a cosmological first-order phase transition occurs sufficiently slowly, delayed vacuum decay may lead to the formation of primordial black holes. Here we consider a simple model as a case study of how the abundance of the produced black holes depe
Externí odkaz:
http://arxiv.org/abs/2412.10666
Autor:
Geng, Yanda, Tao, Junheng, Zhao, Mingshu, Mukherjee, Shouvik, Eckel, Stephen, Campbell, Gretchen K., Spielman, Ian B.
Instabilities, where small fluctuations seed the formation of large-scale structures, govern dynamics in a variety of fluid systems. The Rayleigh-Taylor instability (RTI), present from tabletop to astronomical scales, is an iconic example characteriz
Externí odkaz:
http://arxiv.org/abs/2411.19807
Adversarial audio attacks pose a significant threat to the growing use of large language models (LLMs) in voice-based human-machine interactions. While existing research has primarily focused on model-specific adversarial methods, real-world applicat
Externí odkaz:
http://arxiv.org/abs/2411.14842
Mobile agents are essential for automating tasks in complex and dynamic mobile environments. As foundation models evolve, the demands for agents that can adapt in real-time and process multimodal data have grown. This survey provides a comprehensive
Externí odkaz:
http://arxiv.org/abs/2411.02006
Autor:
Li, Jiafeng, Mu, Yanda
The transcription of medical monologues, especially those containing a high density of specialized terminology and delivered with a distinct accent, presents a significant challenge for existing automated systems. This paper introduces a novel approa
Externí odkaz:
http://arxiv.org/abs/2410.03797
Time-Sensitive Question Answering (TSQA) demands the effective utilization of specific temporal contexts, encompassing multiple time-evolving facts, to address time-sensitive questions. This necessitates not only the parsing of temporal information w
Externí odkaz:
http://arxiv.org/abs/2409.16909
Autor:
Huang, Baoru, Vo, Tuan, Kongtongvattana, Chayun, Dagnino, Giulio, Kundrat, Dennis, Chi, Wenqiang, Abdelaziz, Mohamed, Kwok, Trevor, Jianu, Tudor, Do, Tuong, Le, Hieu, Nguyen, Minh, Nguyen, Hoan, Tjiputra, Erman, Tran, Quang, Xie, Jianyang, Meng, Yanda, Bhattarai, Binod, Tan, Zhaorui, Liu, Hongbin, Gan, Hong Seng, Wang, Wei, Yang, Xi, Wang, Qiufeng, Su, Jionglong, Huang, Kaizhu, Stefanidis, Angelos, Guo, Min, Du, Bo, Tao, Rong, Vu, Minh, Zheng, Guoyan, Zheng, Yalin, Vasconcelos, Francisco, Stoyanov, Danail, Elson, Daniel, Baena, Ferdinando Rodriguez y, Nguyen, Anh
Real-time visual feedback from catheterization analysis is crucial for enhancing surgical safety and efficiency during endovascular interventions. However, existing datasets are often limited to specific tasks, small scale, and lack the comprehensive
Externí odkaz:
http://arxiv.org/abs/2408.13126
With the advancement of Multimodal Large Language Models (MLLM), LLM-driven visual agents are increasingly impacting software interfaces, particularly those with graphical user interfaces. This work introduces a novel LLM-based multimodal agent frame
Externí odkaz:
http://arxiv.org/abs/2408.11824
In this study, we explore an emerging research area of Continual Learning for Temporal Sensitive Question Answering (CLTSQA). Previous research has primarily focused on Temporal Sensitive Question Answering (TSQA), often overlooking the unpredictable
Externí odkaz:
http://arxiv.org/abs/2407.12470
Autor:
Zeng, Qingcheng, Jin, Mingyu, Yu, Qinkai, Wang, Zhenting, Hua, Wenyue, Zhou, Zihao, Sun, Guangyan, Meng, Yanda, Ma, Shiqing, Wang, Qifan, Juefei-Xu, Felix, Ding, Kaize, Yang, Fan, Tang, Ruixiang, Zhang, Yongfeng
Large Language Models (LLMs) are employed across various high-stakes domains, where the reliability of their outputs is crucial. One commonly used method to assess the reliability of LLMs' responses is uncertainty estimation, which gauges the likelih
Externí odkaz:
http://arxiv.org/abs/2407.11282