A Chatbot for Asylum-Seeking Migrants in Europe

• URL: http://arxiv.org/abs/2407.09197v2
• Date: Fri, 27 Sep 2024 14:01:16 GMT
• Title: A Chatbot for Asylum-Seeking Migrants in Europe
• Authors: Bettina Fazzinga, Elena Palmieri, Margherita Vestoso, Luca Bolognini, Andrea Galassi, Filippo Furfaro, Paolo Torroni,
• Abstract summary: ACME aims to help migrants identify the highest level of protection they can apply for. This would contribute to a more sustainable migration by reducing the load on territorial commissions, Courts, and humanitarian organizations supporting asylum applicants.
• Score: 14.060846768281705
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: We present ACME: A Chatbot for asylum-seeking Migrants in Europe. ACME relies on computational argumentation and aims to help migrants identify the highest level of protection they can apply for. This would contribute to a more sustainable migration by reducing the load on territorial commissions, Courts, and humanitarian organizations supporting asylum applicants. We describe the background context, system architecture, underlying technologies, and a case study used to validate the tool with domain experts.

Related papers

• Global Challenge for Safe and Secure LLMs Track 1 [57.08717321907755]
  The Global Challenge for Safe and Secure Large Language Models (LLMs) is a pioneering initiative organized by AI Singapore (AISG) and the CyberSG R&D Programme Office (CRPO) This paper introduces the Global Challenge for Safe and Secure Large Language Models (LLMs), a pioneering initiative organized by AI Singapore (AISG) and the CyberSG R&D Programme Office (CRPO) to foster the development of advanced defense mechanisms against automated jailbreaking attacks.
  arXiv  Detail & Related papers  (2024-11-21T08:20:31Z)
• Evaluating Cultural and Social Awareness of LLM Web Agents [113.49968423990616]
  We introduce CASA, a benchmark designed to assess large language models' sensitivity to cultural and social norms. Our approach evaluates LLM agents' ability to detect and appropriately respond to norm-violating user queries and observations. Experiments show that current LLMs perform significantly better in non-agent environments.
  arXiv  Detail & Related papers  (2024-10-30T17:35:44Z)
• Human-Centered AI Applications for Canada's Immigration Settlement Sector [5.5437761853813665]
  This paper emphasizes the potential of AI in Canada's immigration settlement phase. By highlighting the settlement sector as a prime candidate for reliable AI applications, we demonstrate its unique capacity to empower immigrants directly. We outline a vision for human-centred and responsible AI solutions that facilitate the integration of newcomers.
  arXiv  Detail & Related papers  (2024-09-02T20:52:11Z)
• Combining Twitter and Mobile Phone Data to Observe Border-Rush: The Turkish-European Border Opening [2.5693085674985117]
  Following Turkey's 2020 decision to revoke border controls, many individuals journeyed towards the Greek, Bulgarian, and Turkish borders. However, the lack of verifiable statistics on irregular migration and discrepancies between media reports and actual migration patterns require further exploration. This study is to bridge this knowledge gap by harnessing novel data sources, specifically mobile phone and Twitter data.
  arXiv  Detail & Related papers  (2024-05-21T09:51:15Z)
• Simple Yet Effective Neural Ranking and Reranking Baselines for Cross-Lingual Information Retrieval [50.882816288076725]
  Cross-lingual information retrieval is the task of searching documents in one language with queries in another. We provide a conceptual framework for organizing different approaches to cross-lingual retrieval using multi-stage architectures for mono-lingual retrieval as a scaffold. We implement simple yet effective reproducible baselines in the Anserini and Pyserini IR toolkits for test collections from the TREC 2022 NeuCLIR Track, in Persian, Russian, and Chinese.
  arXiv  Detail & Related papers  (2023-04-03T14:17:00Z)
• SpaceQA: Answering Questions about the Design of Space Missions and Space Craft Concepts [57.012600276711005]
  We present SpaceQA, to the best of our knowledge the first open-domain QA system in Space mission design. SpaceQA is part of an initiative by the European Space Agency (ESA) to facilitate the access, sharing and reuse of information about Space mission design.
  arXiv  Detail & Related papers  (2022-10-07T09:41:39Z)
• Rites de Passage: Elucidating Displacement to Emplacement of Refugees on Twitter [0.7487718119544156]
  We employ a multimodal architecture for probing the refugee journeys from their home to host nations. We collected 0.23 million multimodal tweets from April 2020 to March 2021 for testing this proposed frame-work. We find that a combination of transformer-based language models and state-of-the-art image recognition models, such as fusion of BERT+LSTM and InceptionV4, can out-perform unimodal models.
  arXiv  Detail & Related papers  (2022-05-30T05:12:34Z)
• MISC: A MIxed Strategy-Aware Model Integrating COMET for Emotional Support Conversation [64.37111498077866]
  We propose a novel model for emotional support conversation. It infers the user's fine-grained emotional status, and then responds skillfully using a mixture of strategy. Experimental results on the benchmark dataset demonstrate the effectiveness of our method.
  arXiv  Detail & Related papers  (2022-03-25T10:32:04Z)
• Migratable AI : Investigating users' affect on identity and information migration of a conversational AI agent [25.029958885340058]
  We present a 2x2 between-subjects study in a task-based scenario using information migration and identity migration as parameters. Our results show that users reported highest joy and were most surprised when both the information and identity was migrated; and reported most anger when the information was migrated without the identity of their agent.
  arXiv  Detail & Related papers  (2020-10-22T22:31:34Z)
• Migration and Refugee Crisis: a Critical Analysis of Online Public Perception [2.9005223064604078]
  The migration rate and the level of resentments towards migrants are an important issue in modern civilisation. We analyse sentiment and the associated context of expressions in a vast collection of tweets related to the EU refugee crisis. Our study reveals a marginally higher proportion of negative sentiments vis-a-vis migrants and a large proportion of the negative sentiments is more reflected among the ordinary users.
  arXiv  Detail & Related papers  (2020-07-20T02:04:01Z)
• Enhancing Answer Boundary Detection for Multilingual Machine Reading Comprehension [86.1617182312817]
  We propose two auxiliary tasks in the fine-tuning stage to create additional phrase boundary supervision. A mixed Machine Reading task, which translates the question or passage to other languages and builds cross-lingual question-passage pairs. A language-agnostic knowledge masking task by leveraging knowledge phrases mined from web.
  arXiv  Detail & Related papers  (2020-04-29T10:44:00Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.