Zobrazeno 1 - 10
of 3 633
pro vyhledávání: '"P. P. Padhi"'
Autor:
Lee, Bruce W., Padhi, Inkit, Ramamurthy, Karthikeyan Natesan, Miehling, Erik, Dognin, Pierre, Nagireddy, Manish, Dhurandhar, Amit
LLMs have shown remarkable capabilities, but precisely controlling their response behavior remains challenging. Existing activation steering methods alter LLM behavior indiscriminately, limiting their practical applicability in settings where selecti
Externí odkaz:
http://arxiv.org/abs/2409.05907
Training state-of-the-art (SOTA) deep learning models requires a large amount of data. The visual information present in the training data can be misused, which creates a huge privacy concern. One of the prominent solutions for this issue is perceptu
Externí odkaz:
http://arxiv.org/abs/2407.06570
Large language models (LLMs) have convincing performance in a variety of downstream tasks. However, these systems are prone to generating undesirable outputs such as harmful and biased text. In order to remedy such generations, the development of gua
Externí odkaz:
http://arxiv.org/abs/2407.06323
In this work, we investigate two salient chaotic features, namely Lyapunov exponent and butterfly velocity, in the context of an asymptotically Lifshitz black hole background with an arbitrary critical exponent. These features are computed using thre
Externí odkaz:
http://arxiv.org/abs/2406.18319
The landscape of fake media creation changed with the introduction of Generative Adversarial Networks (GAN s). Fake media creation has been on the rise with the rapid advances in generation technology, leading to new challenges in Detecting fake medi
Externí odkaz:
http://arxiv.org/abs/2406.18278
In this paper, we investigate pulsating string solutions within the context of a two-parameter $\chi$-deformed $\mathcal{R} \times S^2$ background. We derive the energy and oscillation number relation for the deformed $\mathcal{R} \times S^2$ in a sh
Externí odkaz:
http://arxiv.org/abs/2406.17449
Autor:
Hou, Yufang, Pascale, Alessandra, Carnerero-Cano, Javier, Tchrakian, Tigran, Marinescu, Radu, Daly, Elizabeth, Padhi, Inkit, Sattigeri, Prasanna
Retrieval-augmented generation (RAG) has emerged as a promising solution to mitigate the limitations of large language models (LLMs), such as hallucinations and outdated information. However, it remains unclear how LLMs handle knowledge conflicts ari
Externí odkaz:
http://arxiv.org/abs/2406.13805
Large language models (LLMs) have shown to pose social and ethical risks such as generating toxic language or facilitating malicious use of hazardous knowledge. Machine unlearning is a promising approach to improve LLM safety by directly removing har
Externí odkaz:
http://arxiv.org/abs/2406.11780
In recent years, the incorporation of acoustic black holes into Schwarzschild spacetime has enabled the simultaneous existence of event and acoustic horizons, as derived from the Gross-Pitaevskii theory. This paper investigates the dynamics of a part
Externí odkaz:
http://arxiv.org/abs/2405.12337
Autor:
Dognin, Pierre, Rios, Jesus, Luss, Ronny, Padhi, Inkit, Riemer, Matthew D, Liu, Miao, Sattigeri, Prasanna, Nagireddy, Manish, Varshney, Kush R., Bouneffouf, Djallel
Developing value-aligned AI agents is a complex undertaking and an ongoing challenge in the field of AI. Specifically within the domain of Large Language Models (LLMs), the capability to consolidate multiple independently trained dialogue agents, eac
Externí odkaz:
http://arxiv.org/abs/2403.12805