Zobrazeno 1 - 10
of 8 681
pro vyhledávání: '"Sathish, P."'
Autor:
Wu, Tong, Zhang, Shujian, Song, Kaiqiang, Xu, Silei, Zhao, Sanqiang, Agrawal, Ravi, Indurthi, Sathish Reddy, Xiang, Chong, Mittal, Prateek, Zhou, Wenxuan
Large Language Models (LLMs) are susceptible to security and safety threats, such as prompt injection, prompt extraction, and harmful requests. One major cause of these vulnerabilities is the lack of an instruction hierarchy. Modern LLM architectures
Externí odkaz:
http://arxiv.org/abs/2410.09102
The quadratic traveling salesperson problem (QTSP) is a generalization of the traveling salesperson problem, in which all triples of consecutive customers in a tour determine the travel cost. We propose compact optimization models for QTSP in mixed-i
Externí odkaz:
http://arxiv.org/abs/2408.16680
Autor:
Sathish, Sanjay, Sharma, Charu C
Our research presents a new approach for forecasting the synchronization of stock prices using machine learning and non-linear time-series analysis. To capture the complex non-linear relationships between stock prices, we utilize recurrence plots (RP
Externí odkaz:
http://arxiv.org/abs/2409.06728
Autor:
Bhogale, Kaushal Santosh, Mehendale, Deovrat, Parasa, Niharika, G, Sathish Kumar Reddy, Javed, Tahir, Kumar, Pratyush, Khapra, Mitesh M.
In this study, we tackle the challenge of limited labeled data for low-resource languages in ASR, focusing on Hindi. Specifically, we explore pseudo-labeling, by proposing a generic framework combining multiple ideas from existing works. Our framewor
Externí odkaz:
http://arxiv.org/abs/2408.14026
In the context of increasingly complex environmental challenges, effective pollution control mechanisms are crucial. By extending the state of the art auction mechanisms, we aim to develop an efficient approach for allocating pollution abatement reso
Externí odkaz:
http://arxiv.org/abs/2408.10148
Synthetic data is becoming increasingly integral in data-scarce fields such as medical imaging, serving as a substitute for real data. However, its inherent statistical characteristics can significantly impact downstream tasks, potentially compromisi
Externí odkaz:
http://arxiv.org/abs/2407.21674
Autor:
Sathish, Sharath
This paper describes the extensive Wind Tunnel (WT) linear cascade testing campaign carried out on a constant section turbine blade developed for low subsonic applications. Comprehensive experimental program was designed to determine the aerodynamic
Externí odkaz:
http://arxiv.org/abs/2407.11210
Autor:
Indurthi, Sathish Reddy, Zhou, Wenxuan, Chollampatt, Shamil, Agrawal, Ravi, Song, Kaiqiang, Zhao, Lingxiao, Zhu, Chenguang
Advancements in Large Language Models (LLMs) have significantly enhanced instruction-following capabilities. However, most Instruction Fine-Tuning (IFT) datasets are predominantly in English, limiting model performance in other languages. Traditional
Externí odkaz:
http://arxiv.org/abs/2407.01853
Autor:
Zhou, Wenxuan, Agrawal, Ravi, Zhang, Shujian, Indurthi, Sathish Reddy, Zhao, Sanqiang, Song, Kaiqiang, Xu, Silei, Zhu, Chenguang
Reinforcement learning from human feedback (RLHF) is a promising solution to align large language models (LLMs) more closely with human values. Off-policy preference optimization, where the preference data is obtained from other models, is widely ado
Externí odkaz:
http://arxiv.org/abs/2406.11827
Autor:
Mansky, Maximilian Balthasar, Martinez, Miguel Armayor, de la Serna, Alejandro Bravo, Castillo, Santiago Londoño, Nikoladou, Dimitra, Sathish, Gautham, Wang, Zhihao, Wölckert, Sebastian, Linnhoff-Popien, Claudia
The intrinsic symmetries of physical systems have been employed to reduce the number of degrees of freedom of systems, thereby simplifying computations. In this work, we investigate the properties of $\mathcal{M}SU(2^N)$, $\mathcal{M}$-invariant subs
Externí odkaz:
http://arxiv.org/abs/2406.09962