Enhancing Procedural Writing Through Personalized Example Retrieval: A Case Study on Cooking Recipes

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Integer linear programming (ILP) is an elegant approach to solve linear optimization problems, naturally described using integer decision variables. Within the context of physics-inspired machine learning (ML) applied to chemistry, we demonstrate the relev ...

Recommendation systems play a crucial role in providing web-based suggestion utilities by leveraging user behavior, preferences, and interests. In the context of privacy concerns and the proliferation of handheld devices, federated recommender systems have ...

Humans and animals constantly adapt to their environment over the course of their life. This thesis seeks to integrate various timescales of adaptation, ranging from the adaptation of synaptic connections between spiking neurons (milliseconds), rapid behav ...

A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...

Inclusive teaching is the intentional practice of recognising biases, working to mitigate their impact, and ensuring that students have equitable learning opportunities. In addition to improving students' sense of belonging and self efficacy, inclusive tea ...

In this dissertation, we propose multiple methods to improve transfer learning for pretrained language models (PLMs). Broadly, transfer learning is a powerful technique in natural language processing, where a language model is first pre-trained on a data-r ...

Over the past few decades, the debates have shifted from whether to how Computer Science (CS) should be introduced into formal education. Given the diverse ways to introduce CS into formal education, and the struggles many countries have faced, considerabl ...

In recent years, there has been widespread concern about misinformation and hateful content on social media that are damaging societies. Being one of the most influential social media that practically serves as a newsearch engine, YouTube has accepted crit ...

The theory underlying robust distributed learning algorithms, designed to resist adversarial machines, matches empirical observations when data is homogeneous. Under data heterogeneity however, which is the norm in practical scenarios, established lower bo ...

Maximal subgraph mining is increasingly important in various domains, including bioinformatics, genomics, and chemistry, as it helps identify common characteristics among a set of graphs and enables their classification into different categories. Existing ...

The learning process depends on the nature of the learning environment, particularly in the case of open-ended learning environments, where the learning process is considered to be non-linear. In this paper, we report on the findings of employing a multimo ...

Intelligence involves processing sensory experiences into representations useful for prediction. Understanding sensory experiences and building these contextual representations without prior knowledge of sensor models and environment is a challenging unsup ...

The trend towards generalized blended and active learning approaches in engineering education is redefining the requirements and the deployment schemes for digital education platforms. This paper presents a quadriptych techno- pedagogical model highlightin ...

Student peer review writing is prevalent and important in education for fostering critical thinking and learning motivation. However, it often entails challenges such as high effort and writer's block. Leaving students unsupported may thus diminish the eff ...

Computational thinking (CT) skills are becoming increasingly relevant for future professionals across all domains, beyond computer science (CS). As such, an increasing number of bachelor and masters programs outside of the computer science discipline integ ...

In this paper, we introduce a new solution and underlying architecture that allows remote participants to interact with hosts in a broadcast scenario. To achieve this, background extraction is first applied to video received from remote participants to ext ...

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 ...

The field of text-to-video retrieval has advanced significantly with the evolution of language models and large-scale pre-training on generated caption-video pairs. Current methods predominantly focus on visual and event-based details, making retrieval lar ...

Unsupervised self-rehabilitation exercises and physical training can cause serious injuries if performed incorrectly. We introduce a learning-based framework that identifies the mistakes made by a user and proposes corrective measures for easier and safer ...

Students learn more when they are actively engaged in the learning process. While hands-on activities, labs and projects are moments when students are active, the learning benefits can be amplified with coaching strategies. This activity will enable studen ...

Enhancing Procedural Writing Through Personalized Example Retrieval: A Case Study on Cooking Recipes

Chattez avec Graph Search

Integer Linear Programming for Unsupervised Training Set Selection in Molecular Machine Learning

Certified Unlearning for Federated Recommendation

From event-based surprise to lifelong learning. A journey in the timescales of adaptation

incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment

Inclusive engineering classrooms: student teaching assistants' perspectives

Improving Generalization of Pretrained Language Models

Co-constructing an Effective, Sustainable and Scalable Primary School Computer Science Curricular Reform

Referencing in YouTube Knowledge Communication Videos

Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity

Scalable maximal subgraph mining with backbone-preserving graph convolutions

Temporal Pathways to Learning: How Learning Emerges in an Open-ended Collaborative Activity

Mechanical intelligence for learning embodied sensor-object relationships

Integrated Model for Comprehensive Digital Education Platforms

Intelligent Support Engages Writers Through Relevant Cognitive Processes

Promoting Computational Thinking Skills in Non-Computer Science Students Gamifying Computational Notebooks to Increase Student Engagement

AI-based telepresence for broadcast applications

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

Beyond Essentials: Nuanced and Diverse Text-to-video Retrieval

3D Pose Based Feedback For Physical Exercises

How to support students to develop coaching and peer teaching skills