2024
Authors
Piskorski, J; Stefanovitch, N; Alam, F; Campos, R; Dimitrov, D; Jorge, A; Pollak, S; Ribin, N; Fijavz, Z; Hasanain, M; Silvano, P; Sartori, E; Guimarães, N; Vitez, AZ; Pacheco, AF; Koychev, I; Yu, N; Nakov, P; San Martino, GD;
Publication
CLEF (Working Notes)
Abstract
We present an overview of CheckThat! Lab's 2024 Task 3, which focuses on detecting 23 persuasion techniques at the text-span level in online media. The task covers five languages, namely, Arabic, Bulgarian, English, Portuguese, and Slovene, and highly-debated topics in the media, e.g., the Isreali-Palestian conflict, the Russia-Ukraine war, climate change, COVID-19, abortion, etc. A total of 23 teams registered for the task, and two of them submitted system responses which were compared against a baseline and a task organizers' system, which used a state-of-the-art transformer-based architecture. We provide a description of the dataset and the overall task setup, including the evaluation methodology, and an overview of the participating systems. The datasets accompanied with the evaluation scripts are released to the research community, which we believe will foster research on persuasion technique detection and analysis of online media content in various fields and contexts.
2024
Authors
Baghcheband, H; Soares, C; Reis, LP;
Publication
IEEE INTERNET COMPUTING
Abstract
Today, autonomous agents, the Internet of Things, and smart devices produce more and more distributed data and use them to learn models for different purposes. One challenge is that learning from local data only may lead to suboptimal models. Thus, better models are expected if agents can exchange data, leading to approaches such as federated learning. However, these approaches assume that data have no value and, thus, is exchanged for free. A machine learning data market (MLDM), a framework based on multiagent systems with a market-based perspective on data exchange, was recently proposed. In an MLDM, each agent trains its model based on both local data and data bought from other agents. Although the empirical results are interesting, several challenges are still open, including data acquisition and data valuation. The MLDM is an illustrative example of how the value of data can and should be integrated into the design of distributed ML systems.
2024
Authors
Vanhoucke, M; Coelho, J;
Publication
COMPUTERS & OPERATIONS RESEARCH
Abstract
This paper present an instance transformation procedure to modify known instances of the resource -constrained project scheduling problem to make them easier to solve by heuristic and/or exact solution algorithms. The procedure makes use of a set of transformation rules that aim at reducing the feasible search space without excluding at least one possible optimal solution. The procedure will be applied to a set of 11,183 instances and it will be shown by a set of experiments that these transformations lead to 110 improved lower bounds, 16 new and better schedules (found by three meta -heuristic procedures and a set of branch -and -bound procedures) and even 64 new optimal solutions which were never not found before.
2024
Authors
Hill, RK; Baquero, C;
Publication
Commun. ACM
Abstract
2024
Authors
Azevedo, C; Roxo, MT; Brandão, A;
Publication
Smart Innovation, Systems and Technologies
Abstract
This study develops some sustainable tourism advertising effects and consumer environmental awareness-raising and examines them by advertising certification and advertising format in a field experiment. The tourism advertising effects are analyzed by five dependent variables: trust and credibility, environmentalism, ad relevance, realism, and flow. Several ANOVA and multiple comparison tests were performed to understand whether these variables varied between groups. Experimental research findings indicate that flow and video format affect tourism advertising and consumer environmental awareness-raising. This study demonstrates the importance of understanding the concept of sustainable tourism and awareness-raising. It also points to identifying the best communication strategies to promote a sustainable destination, as different communication methods may lead to different results. In addition, it provides valuable information for marketers to consider when implementing their communication strategies. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
2024
Authors
Vérinaud, C; Héritier, CT; Kasper, M; Haffert, S; Snik, F; Doelman, D; Carlotti, A; Engler, B; Le Louarn, M; Correia, C; Tallon, M;
Publication
ADAPTIVE OPTICS SYSTEMS IX
Abstract
Resolution and sensitivity of the wavefront sensor (WFS) are key requirements for eXtreme Adaptive Optics (XAO) applications. We present a new class of WFSs, the Bi-Orthogonal Foucault-knife-edge (Bi-O edge), that is directly inspired by the Foucault knife-edge test. The idea consists of using a beam-splitter producing two foci, each of which is sensed by an edge with an orthogonal direction to the other. We describe two implementation concepts. The first one, the tip-tilt modulated sharp Bi-O-edge, can be seen as a mild evolution of the Pyramid. The second one uses a smooth, gradual amplitude mask over a 'grey' zone on the edge (grey Bi-O edge). We analyze the increased gain in sensitivity and the super-resolution capability, we compare these properties to the Pyramid sensor and produce end-to-end simulations. An important advantage of the grey Bi-O edge is the static modulation which is well adapted for fast XAO systems. The grey edge consists of a rectangular zone on the edge of the same size as the modulation circle. We will discuss the manufacturability of loss-less grey Foucault-knife edges, and we develop a polarization-based technique for the Bi-O edge prototype for the ESO GHOST test bench.
The access to the final selection minute is only available to applicants.
Please check the confirmation e-mail of your application to obtain the access code.