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The rapid rise of Large Language Models (LLMs) has created new disruptive possibilities for persuasive communication, by enabling fully-automated personalized and interactive content generation at an unprecedented scale. In this paper, we survey the
Externí odkaz:
http://arxiv.org/abs/2411.06837
Autor:
Buyl, Maarten, Rogiers, Alexander, Noels, Sander, Dominguez-Catena, Iris, Heiter, Edith, Romero, Raphael, Johary, Iman, Mara, Alexandru-Cristian, Lijffijt, Jefrey, De Bie, Tijl
Large language models (LLMs) are trained on vast amounts of data to generate natural language, enabling them to perform tasks like text summarization and question answering. These models have become popular in artificial intelligence (AI) assistants
Externí odkaz:
http://arxiv.org/abs/2410.18417
This paper presents FinGEITje, the first Dutch financial Large Language Model (LLM) specifically designed and optimized for various financial tasks. Together with the model, we release a specialized Dutch financial instruction tuning dataset with ove
Externí odkaz:
http://arxiv.org/abs/2410.12835
Numerous methods have been implemented that pursue fairness with respect to sensitive features by mitigating biases in machine learning. Yet, the problem settings that each method tackles vary significantly, including the stage of intervention, the c
Externí odkaz:
http://arxiv.org/abs/2409.16965
In this paper, we show that a Clifford algebra valued function is slice if and only if it is in the kernel of Dunkl-spherical Dirac operator and a slice function $f$ is slice regular if and only if it is in the kernel of the Dunkl-Cauchy-Riemann oper
Externí odkaz:
http://arxiv.org/abs/2407.06811
Autor:
Heiter, Edith, Martens, Liesbet, Seurinck, Ruth, Guilliams, Martin, De Bie, Tijl, Saeys, Yvan, Lijffijt, Jefrey
This paper presents TRACE, a tool to analyze the quality of 2D embeddings generated through dimensionality reduction techniques. Dimensionality reduction methods often prioritize preserving either local neighborhoods or global distances, but insights
Externí odkaz:
http://arxiv.org/abs/2406.12953
Personalized recommendation systems often drive users towards more extreme content, exacerbating opinion polarization. While (content-aware) moderation has been proposed to mitigate these effects, such approaches risk curtailing the freedom of speech
Externí odkaz:
http://arxiv.org/abs/2405.18941
Publikováno v:
IEEE Access ( Volume: 11, 2023) Page(s): 117971 - 117983
Representing the nodes of continuous-time temporal graphs in a low-dimensional latent space has wide-ranging applications, from prediction to visualization. Yet, analyzing continuous-time relational data with timestamped interactions introduces uniqu
Externí odkaz:
http://arxiv.org/abs/2405.17253
Publikováno v:
Appl. Sci. 2024, 14(8), 3516
Dynamic Link Prediction (DLP) addresses the prediction of future links in evolving networks. However, accurately portraying the performance of DLP algorithms poses challenges that might impede progress in the field. Importantly, common evaluation pip
Externí odkaz:
http://arxiv.org/abs/2405.17182
KamerRaad is an AI tool that leverages large language models to help citizens interactively engage with Belgian political information. The tool extracts and concisely summarizes key excerpts from parliamentary proceedings, followed by the potential f
Externí odkaz:
http://arxiv.org/abs/2404.17597