Zobrazeno 1 - 10
of 11 766
pro vyhledávání: '"Verbruggen, A. A."'
Autor:
Minucci, Franco, Oishi, Raquel Marina Noguera, Xiong, Haoqiu, Verbruggen, Dieter, Thys, Cel, Hersyandika, Rizqi, Beerten, Robbert, Colpaert, Achiel, Ranjbar, Vida, Pollin, Sofie
This work describes the architecture and vision of designing and implementing a new test infrastructure for 6G physical layer research at KU Leuven. The Testbed is designed for physical layer research and experimentation following several emerging tr
Externí odkaz:
http://arxiv.org/abs/2410.01298
Autor:
Singh, Usneek, Cambronero, José, Gulwani, Sumit, Kanade, Aditya, Khatry, Anirudh, Le, Vu, Singh, Mukul, Verbruggen, Gust
Large language models (LLMs) can be leveraged to help with writing formulas in spreadsheets, but resources on these formulas are scarce, impacting both the base performance of pre-trained models and limiting the ability to fine-tune them. Given a cor
Externí odkaz:
http://arxiv.org/abs/2407.10657
Deep learning (DL) techniques are increasingly pervasive across various domains, including wireless communication, where they extract insights from raw radio signals. However, the computational demands of DL pose significant challenges, particularly
Externí odkaz:
http://arxiv.org/abs/2405.03222
Autor:
Singha, Ananya, Chopra, Bhavya, Khatry, Anirudh, Gulwani, Sumit, Henley, Austin Z., Le, Vu, Parnin, Chris, Singh, Mukul, Verbruggen, Gust
Automated insight generation is a common tactic for helping knowledge workers, such as data scientists, to quickly understand the potential value of new and unfamiliar data. Unfortunately, automated insights produced by large-language models can gene
Externí odkaz:
http://arxiv.org/abs/2405.01556
In the evolution of 6th Generation (6G) technology, the emergence of cell-free networking presents a paradigm shift, revolutionizing user experiences within densely deployed networks where distributed access points collaborate. However, the integrati
Externí odkaz:
http://arxiv.org/abs/2403.08563
Multi-modality promises to unlock further uses for large language models. Recently, the state-of-the-art language model GPT-4 was enhanced with vision capabilities. We carry out a prompting evaluation of GPT-4V and five other baselines on structured
Externí odkaz:
http://arxiv.org/abs/2312.11524
Imagine a developer who can only change their last line of code, how often would they have to start writing a function from scratch before it is correct? Auto-regressive models for code generation from natural language have a similar limitation: they
Externí odkaz:
http://arxiv.org/abs/2310.17680
Autor:
Singh, Mukul, Cambronero, José, Gulwani, Sumit, Le, Vu, Negreanu, Carina, Nouri, Elnaz, Raza, Mohammad, Verbruggen, Gust
Formatting is an important property in tables for visualization, presentation, and analysis. Spreadsheet software allows users to automatically format their tables by writing data-dependent conditional formatting (CF) rules. Writing such rules is oft
Externí odkaz:
http://arxiv.org/abs/2310.17306
Autor:
Khatry, Anirudh, Gulwani, Sumit, Gupta, Priyanshu, Le, Vu, Singha, Ananya, Singh, Mukul, Verbruggen, Gust
Target similarity tuning (TST) is a method of selecting relevant examples in natural language (NL) to code generation through large language models (LLMs) to improve performance. Its goal is to adapt a sentence embedding model to have the similarity
Externí odkaz:
http://arxiv.org/abs/2310.17228
String data is common in real-world datasets: 67.6% of values in a sample of 1.8 million real Excel spreadsheets from the web were represented as text. Systems that successfully clean such string data can have a significant impact on real users. Whil
Externí odkaz:
http://arxiv.org/abs/2308.10922