Delve into the cutting edge of Artificial Intelligence with our dedicated Research Paper section.
![Determinants of renewable energy consumption in Madagascar: Evidence from feature selection algorithms. (arXiv:2401.13671v1 [econ.GN])](http://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png "Determinants of renewable energy consumption in Madagascar: Evidence from feature selection algorithms. (arXiv:2401.13671v1 [econ.GN])"){kind=logo}
The aim of this note is to identify the factors influencing renewable energy consumption in Madagascar. We tested 12 features covering macroeconomic, financial, social, and environmental aspects, including economic growth, domestic investment, foreign direct investment, financial development, industrial development, inflation,…
Deploying neural networks on microcontroller units (MCUs) presents substantial challenges due to their constrained computation and memory resources. Previous researches have explored patch-based inference as a strategy to conserve memory without sacrificing model accuracy. However, this technique suffers from severe…
Existing multimodal sentiment analysis tasks are highly rely on the assumption that the training and test sets are complete multimodal data, while this assumption can be difficult to hold: the multimodal data are often incomplete in real-world scenarios. Therefore, a…
The need to understand the structure of hierarchical or high-dimensional data is present in a variety of fields. Hyperbolic spaces have proven to be an important tool for embedding computations and analysis tasks as their non-linear nature lends itself well…
Avalanche: A PyTorch Library for Deep Continual Learning Antonio Carta, Lorenzo Pellegrini, Andrea Cossu, Hamed Hemati, Vincenzo Lomonaco; 24(363):1−6, 2023. Abstract Continual learning is the problem of learning from a nonstationary stream of data, a fundamental issue for sustainable and…
Public opinion surveys are vital for informing democratic decision-making, but responding to rapidly changing information environments and measuring beliefs within niche communities can be challenging for traditional survey methods. This paper introduces a crowdsourced adaptive survey methodology (CSAS) that unites…
Emotion Recognition in Conversation (ERC) plays a crucial role in enabling dialogue systems to effectively respond to user requests. The emotions in a conversation can be identified by the representations from various modalities, such as audio, visual, and text. However,…
This paper presents a novel generative model, Collaborative Competitive Agents (CCA), which leverages the capabilities of multiple Large Language Models (LLMs) based agents to execute complex tasks. Drawing inspiration from Generative Adversarial Networks (GANs), the CCA system employs two equal-status…
Femicide refers to the killing of a female victim, often perpetrated by an intimate partner or family member, and is also associated with gender-based violence. Studies have shown that there is a pattern of escalating violence leading up to these…
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy.…
Flexible Model Aggregation for Quantile Regression Rasool Fakoor, Taesup Kim, Jonas Mueller, Alexander J. Smola, Ryan J. Tibshirani; 24(162):1−45, 2023. Abstract Quantile regression is a fundamental problem in statistical learning motivated by a need to quantify uncertainty in predictions, or…
This study is a pioneering endeavor to investigate the capabilities of Large Language Models (LLMs) in addressing conceptual questions within the domain of mechanical engineering with a focus on mechanics. Our examination involves a manually crafted exam encompassing 126 multiple-choice…