Zobrazeno 1 - 10
of 2 464
pro vyhledávání: '"A. Rényi"'
Building the radio sky template are crucial for detecting the 21 cm emission line signal from the Epoch of Reionization (EoR), as well as for other cosmological research endeavors. Utilizing data from the LOFAR Two-meter Sky Survey (LoTSS) at 150 MHz
Externí odkaz:
http://arxiv.org/abs/2411.03931
Autor:
Bao, Forrest Sheng, Li, Miaoran, Qu, Renyi, Luo, Ge, Wan, Erana, Tang, Yujia, Fan, Weisi, Tamber, Manveer Singh, Kazi, Suleman, Sourabh, Vivek, Qi, Mike, Tu, Ruixuan, Xu, Chenyu, Gonzales, Matthew, Mendelevitch, Ofer, Ahmad, Amin
Summarization is one of the most common tasks performed by large language models (LLMs), especially in applications like Retrieval-Augmented Generation (RAG). However, existing evaluations of hallucinations in LLM-generated summaries, and evaluations
Externí odkaz:
http://arxiv.org/abs/2410.13210
Recent advances in Retrieval-Augmented Generation (RAG) systems have popularized semantic chunking, which aims to improve retrieval performance by dividing documents into semantically coherent segments. Despite its growing adoption, the actual benefi
Externí odkaz:
http://arxiv.org/abs/2410.13070
Autor:
Yang, Renyi
In the expanding field of generative artificial intelligence, integrating robust watermarking technologies is essential to protect intellectual property and maintain content authenticity. Traditionally, watermarking techniques have been developed pri
Externí odkaz:
http://arxiv.org/abs/2410.10178
Developers use logging statements to monitor software, but misleading logs can complicate maintenance by obscuring actual activities. Existing research on logging quality issues is limited, mainly focusing on single defects and manual fixes. To addre
Externí odkaz:
http://arxiv.org/abs/2408.03101
Autor:
Qu, Renyi, Yatskar, Mark
(Renyi Qu's Master's Thesis) Recent advancements in interpretable models for vision-language tasks have achieved competitive performance; however, their interpretability often suffers due to the reliance on unstructured text outputs from large langua
Externí odkaz:
http://arxiv.org/abs/2405.18672
Autor:
Kuang, Jinxi, Liu, Jinyang, Huang, Junjie, Zhong, Renyi, Gu, Jiazhen, Yu, Lan, Tan, Rui, Yang, Zengyin, Lyu, Michael R.
Due to the scale and complexity of cloud systems, a system failure would trigger an "alert storm", i.e., massive correlated alerts. Although these alerts can be traced back to a few root causes, the overwhelming number makes it infeasible for manual
Externí odkaz:
http://arxiv.org/abs/2403.06485
Coordinate-based neural implicit representation or implicit fields have been widely studied for 3D geometry representation or novel view synthesis. Recently, a series of efforts have been devoted to accelerating the speed and improving the quality of
Externí odkaz:
http://arxiv.org/abs/2402.14415
Autor:
Li, Yichen, Huo, Yintong, Zhong, Renyi, Jiang, Zhihan, Liu, Jinyang, Huang, Junjie, Gu, Jiazhen, He, Pinjia, Lyu, Michael R.
Logging practices have been extensively investigated to assist developers in writing appropriate logging statements for documenting software behaviors. Although numerous automatic logging approaches have been proposed, their performance remains unsat
Externí odkaz:
http://arxiv.org/abs/2402.12958
Autor:
Li, Yichen, Huo, Yintong, Jiang, Zhihan, Zhong, Renyi, He, Pinjia, Su, Yuxin, Briand, Lionel, Lyu, Michael R.
Automated logging statement generation supports developers in documenting critical software runtime behavior. Given the great success in natural language generation and programming language comprehension, large language models (LLMs) might help devel
Externí odkaz:
http://arxiv.org/abs/2307.05950