Papers with NGOs
GenDLN: Evolutionary Algorithm-Based Stacked LLM Framework for Joint Prompt Optimization (2025.acl-srw)
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| Challenge: | Large Language Models (LLMs) are increasingly replacing traditional classification and inference models due to their generality, ability to perform a wide range of tasks, and seemingly advanced "reasoning" prompt optimization is a promising alternative to manual/human prompt engineering, but the cost of using LLMs for prompt optimization via commercial APIs remains high. |
| Approach: | They propose an open-source, efficient genetic algorithm-based prompt pair optimization framework that leverages commercial APIs. |
| Outcome: | The proposed approach allows teams with limited resources to efficiently use commercial LLMs for prompt optimization. |
European Language Resource Coordination: Collecting Language Resources for Public Sector Multilingual Information Management (L18-1)
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Andrea Lösch, Valérie Mapelli, Stelios Piperidis, Andrejs Vasiļjevs, Lilli Smal, Thierry Declerck, Eileen Schnur, Khalid Choukri, Josef van Genabith
| Challenge: | European Language Resource Coordination (ELRC) initiated a number of actions to support the collection of Language Resources (LRs) within the public sector in EU member and CEF-affiliated countries. |
| Approach: | They propose to initiate actions to support the collection of Language Resources (LRs) within the public sector in EU member and CEF-affiliated countries. |
| Outcome: | The European Language Resource Coordination (ELRC) consortium initiated a number of actions to support the collection of Language Resources (LRs) within the public sector in EU member and CEF-affiliated countries. |
CONAN - COunter NArratives through Nichesourcing: a Multilingual Dataset of Responses to Fight Online Hate Speech (P19-1)
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| Challenge: | Davidson et al., 2017): social media platforms and governmental organizations have taken steps to tackle hate speech . Davidson and Norton, 2017: a dataset of hate-speech/counter-narrative pairs is created . authors: identifying hate speech is challenging for the broadness and nuances in cultures and languages . |
| Approach: | They propose to build a large-scale, multilingual, expert-based dataset of hate-speech/counter-narrative pairs . they provide additional annotations about expert demographics, hate and response type . |
| Outcome: | The proposed dataset provides an analysis of hate-speech/counter-narrative pairs in three languages. |
Swiss-AL: A Multilingual Swiss Web Corpus for Applied Linguistics (2020.lrec-1)
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| Challenge: | Swiss-AL is a multilingual web corpus for Applied Linguistics that supports data-based and data-driven research on societal and political discourses in Switzerland. |
| Approach: | They propose a multilingual Swiss web corpus for Applied Linguistics that supports data-based research on societal and political discourses in Switzerland. |
| Outcome: | The Swiss Web Corpus for Applied Linguistics (SWS) is a multilingual collection of texts from selected web sources. |
Human-Machine Collaboration Approaches to Build a Dialogue Dataset for Hate Speech Countering (2022.emnlp-main)
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| Challenge: | a new approach to combat online hate speech is being proposed for NLG . existing methods to train NLG are limited to 2-turn interactions, while in real life, interactions can consist of multiple turns. |
| Approach: | They propose to combine human annotators with machine generated dialogues to create a dataset . DIALOCONAN is the first dataset comprising over 3000 fictitious multi-turn dialogues . |
| Outcome: | The proposed approach combines human experts over machine generated dialogues . it is the first dataset comprising over 3000 fictitious multi-turn dialogues between a hater and an NGO operator . |