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pro vyhledávání: '"P Sastry"'
Autonomous racing extends beyond the challenge of controlling a racecar at its physical limits. Professional racers employ strategic maneuvers to outwit other competing opponents to secure victory. While modern control algorithms can achieve human-le
Externí odkaz:
http://arxiv.org/abs/2412.08855
Autor:
Maheshwari, Chinmay, Mendoza, Maria G., Tuck, Victoria Marie, Su, Pan-Yang, Qin, Victor L., Seshia, Sanjit A., Balakrishnan, Hamsa, Sastry, Shankar
Advanced Air Mobility (AAM) operations are expected to transform air transportation while challenging current air traffic management practices. By introducing a novel market-based mechanism, we address the problem of on-demand allocation of capacity-
Externí odkaz:
http://arxiv.org/abs/2411.03582
We present TaxaBind, a unified embedding space for characterizing any species of interest. TaxaBind is a multimodal embedding space across six modalities: ground-level images of species, geographic location, satellite image, text, audio, and environm
Externí odkaz:
http://arxiv.org/abs/2411.00683
Publikováno v:
16th International Conference on Advances in Social Networks Analysis and Mining -ASONAM-2024
Recent studies have outlined the accessibility challenges faced by blind or visually impaired, and less-literate people, in interacting with social networks, in-spite of facilitating technologies such as monotone text-to-speech (TTS) screen readers a
Externí odkaz:
http://arxiv.org/abs/2410.19199
Radio frequency (RF) communication has been an important part of civil and military communication for decades. With the increasing complexity of wireless environments and the growing number of devices sharing the spectrum, it has become critical to e
Externí odkaz:
http://arxiv.org/abs/2410.18283
Autor:
Dumpala, Sri Harsha, Jaiswal, Aman, Sastry, Chandramouli, Milios, Evangelos, Oore, Sageev, Sajjad, Hassan
Despite the significant influx of prompt-tuning techniques for generative vision-language models (VLMs), it remains unclear how sensitive these models are to lexical and semantic alterations in prompts. In this paper, we evaluate the ability of gener
Externí odkaz:
http://arxiv.org/abs/2410.13030
Autor:
Chen, Zixuan, He, Xialin, Wang, Yen-Jen, Liao, Qiayuan, Ze, Yanjie, Li, Zhongyu, Sastry, S. Shankar, Wu, Jiajun, Sreenath, Koushil, Gupta, Saurabh, Peng, Xue Bin
Reinforcement learning combined with sim-to-real transfer offers a general framework for developing locomotion controllers for legged robots. To facilitate successful deployment in the real world, smoothing techniques, such as low-pass filters and sm
Externí odkaz:
http://arxiv.org/abs/2410.11825
Deep Reinforcement Learning (DRL) has been highly effective in learning from and adapting to RF environments and thus detecting and mitigating jamming effects to facilitate reliable wireless communications. However, traditional DRL methods are suscep
Externí odkaz:
http://arxiv.org/abs/2410.10521
Autor:
Demir, Utku, Davaslioglu, Kemal, Sagduyu, Yalin E., Erpek, Tugba, Anderson, Gustave, Kompella, Sastry
Integrated Sensing and Communication (ISAC) represents a transformative approach within 5G and beyond, aiming to merge wireless communication and sensing functionalities into a unified network infrastructure. This integration offers enhanced spectrum
Externí odkaz:
http://arxiv.org/abs/2410.08999
Autor:
Wang, Zeqiang, Wu, Jiageng, Wang, Yuqi, Wang, Wei, Yang, Jie, Johnson, Jon, Sastry, Nishanth, De, Suparna
Social media is recognized as an important source for deriving insights into public opinion dynamics and social impacts due to the vast textual data generated daily and the 'unconstrained' behavior of people interacting on these platforms. However, s
Externí odkaz:
http://arxiv.org/abs/2410.08352