Publications associées à Symbolic artificial intelligence

Revisiting Character-level Adversarial Attacks for Language Models

Volkan Cevher, Grigorios Chrysos, Fanghui Liu, Yongtao Wu, Elias Abad Rocamora

Adversarial attacks in Natural Language Processing apply perturbations in the character or token levels. Token-level attacks, gaining prominence for their use of gradient-based methods, are susceptible to altering sentence semantics, leading to invalid adv ...

2024

MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning

Alexandre Massoud Alahi, Mohamed Ossama Ahmed Abdelfattah, Mariam Ahmed Mahmoud Hegazy Hassan

Current transformer-based skeletal action recognition models tend to focus on a limited set of joints and low-level motion patterns to predict action classes. This results in significant performance degradation under small skeleton perturbations or changin ...

2024

Domain adaptation via alignment of operation profile for Remaining Useful Lifetime prediction

Olga Fink, Ismail Nejjar, Mengjie Zhao

Effective Prognostics and Health Management (PHM) relies on accurate prediction of the Remaining Useful Life (RUL). Data-driven RUL prediction techniques rely heavily on the representativeness of the available time-to-failure trajectories. Therefore, these ...

2024

GELEX: Generative AI-Hybrid System for Example-Based Learning

Jibril Albachir Frej, Aybars Yazici

Traditional example-based learning methods are often limited by static, expert-created content. Hence, they face challenges in scalability, engagement, and effectiveness, as some learners might struggle to relate to the examples or find them relevant. To a ...

Association for Computing Machinery2024

Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model

Yi Zhang, Wenlong Liao, Zhe Yang

Recently, remarkable progress has been made in the application of machine learning (ML) techniques (e.g., neural networks) to transformer fault diagnosis. However, the diagnostic processes employed by these techniques often suffer from a lack of interpreta ...

Piscataway2024

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch

David Atienza Alonso, José Angel Miranda Calero, Jonathan Dan, Christodoulos Kechris

Accurate extraction of heart rate from photoplethysmography (PPG) signals remains challenging due to motion artifacts and signal degradation. Although deep learning methods trained as a data-driven inference problem offer promising solutions, they often un ...

2024

PEACOK: Persona Commonsense Knowledge for Consistent and Engaging Narratives

Antoine Bosselut, Beatriz Maria Borges Ribeiro, Silin Gao, Deniz Bayazit, Soyoung Oh

Sustaining coherent and engaging narratives requires dialogue or storytelling agents to understand how the personas of speakers or listeners ground the narrative. Specifically, these agents must infer personas of their listeners to produce statements that ...

Assoc Computational Linguistics-Acl2023

Let's move forward: Image-computable models and a common model evaluation scheme are prerequisites for a scientific understanding of human vision

Martin Schrimpf, Matthias Bethge

In the target article, Bowers et al. dispute deep artificial neural network (ANN) models as the currently leading models of human vision without producing alternatives. They eschew the use of public benchmarking platforms to compare vision models with the ...

Cambridge2023

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Symbolic artificial intelligence

Revisiting Character-level Adversarial Attacks for Language Models

MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning

Domain adaptation via alignment of operation profile for Remaining Useful Lifetime prediction

GELEX: Generative AI-Hybrid System for Example-Based Learning

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch

Monotonicity Reasoning in the Age of Neural Foundation Models

PEACOK: Persona Commonsense Knowledge for Consistent and Engaging Narratives

Let's move forward: Image-computable models and a common model evaluation scheme are prerequisites for a scientific understanding of human vision

Graph Chatbot

Chattez avec Graph Search

Revisiting Character-level Adversarial Attacks for Language Models

Domain adaptation via alignment of operation profile for Remaining Useful Lifetime prediction

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning

Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model

Let's move forward: Image-computable models and a common model evaluation scheme are prerequisites for a scientific understanding of human vision

Monotonicity Reasoning in the Age of Neural Foundation Models

PEACOK: Persona Commonsense Knowledge for Consistent and Engaging Narratives

KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch

GELEX: Generative AI-Hybrid System for Example-Based Learning