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pro vyhledávání: '"Saseendran, Amrutha"'
Autor:
Gema, Aryo Pradipta, Jin, Chen, Abdulaal, Ahmed, Diethe, Tom, Teare, Philip, Alex, Beatrice, Minervini, Pasquale, Saseendran, Amrutha
Large Language Models (LLMs) often hallucinate, producing unfaithful or factually incorrect outputs by misrepresenting the provided context or incorrectly recalling internal knowledge. Recent studies have identified specific attention heads within th
Externí odkaz:
http://arxiv.org/abs/2410.18860
Textural Inversion, a prompt learning method, learns a singular text embedding for a new "word" to represent image style and appearance, allowing it to be integrated into natural language sentences to generate novel synthesised images. However, ident
Externí odkaz:
http://arxiv.org/abs/2310.12274
Image generation has rapidly evolved in recent years. Modern architectures for adversarial training allow to generate even high resolution images with remarkable quality. At the same time, more and more effort is dedicated towards controlling the con
Externí odkaz:
http://arxiv.org/abs/2103.16795
Publikováno v:
MATEC Web of Conferences, Vol 401, p 07007 (2024)
The hybrid photovoltaic/thermoelectric generator (PV/TEG) technology is an advanced and efficient technology that combines the power from PV and TEGs to generate sustainable electricity. This hybrid approach optimizes energy output and ensures cleane
Externí odkaz:
https://doaj.org/article/dbc3b347b5f44ca197c443e2ef6eaae5
Autor:
Saseendran, Amrutha
The ability of the robot to sense its environment is essential for its autonomous operation. Precise object detection and pose estimation, derived from the sensing capabilities, is crucial for the autonomy of any robotic system. Deep learning and neu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1640::438309077f96d346a16d65d54c3c3709
https://elib.dlr.de/131943/
https://elib.dlr.de/131943/