Papers with policymakers
SpiritRAG: A Q&A System for Religion and Spirituality in the United Nations Archive (2025.emnlp-demos)
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Yingqiang Gao, Fabian Winiger, Patrick Montjourides, Anastassia Shaitarova, Nianlong Gu, Simon Peng-Keller, Gerold Schneider
| Challenge: | Religion and spirituality (R/S) are complex and domain-dependent concepts that have long confounded researchers and policymakers. |
| Approach: | They propose an interactive question-answering system based on Retrieval-Augmented Generation (RAG) SpiritRAG allows researchers and policymakers to conduct complex, context-sensitive database searches of large datasets . |
| Outcome: | SpiritRAG is an interactive Q&A system based on Retrieval-Augmented Generation (RAG) built using 7,500 UN resolution documents related to religion and spirituality in the domains of health and education. |
ClinicalTrialsHub: Bridging Registries and Literature for Comprehensive Clinical Trial Access (2026.eacl-demo)
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Jiwoo Park, Ruoqi Liu, Avani Jagdale, Andrew Srisuwananukorn, Jing Zhao, Lang Li, Ping Zhang, Sachin Kumar
| Challenge: | ClinicalTrialsHub consolidates clinical trial data from ClinicalTrial.gov and augments it by extracting and structuring trial-relevant information from PubMed. |
| Approach: | They propose a search-focused platform that consolidates PubMed data and extracts structured trial information. |
| Outcome: | ClinicalTrialsHub increases access to structured clinical trial data by 83.8% compared to ClinicalTrial.gov alone. |
Communication as a Complex System: Modeling the Feedback Dynamics of Trust and Credibility (2026.eacl-srw)
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| Challenge: | A scoping literature review synthesized disparate communication models from media studies, science communication, psychology, and information science to identify a shared set of system variables. |
| Approach: | The study synthesized disparate communication models from media studies, science communication, psychology, and information science to identify a shared set of system variables. |
| Outcome: | The proposed framework provides a foundation for future system dynamics modeling to examine how interventions in transparency, media literacy, or platform governance may influence public trust over time. |
Content-based Popularity Prediction of Online Petitions Using a Deep Regression Model (P18-2)
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| Challenge: | Existing work on predicting popularity of online petitions based on initial popularity trajectory has focused on estimating the number of signatures a petition gets in the first x hours, and predicting the total number of signed petitions at the end of its lifetime. |
| Approach: | They propose a CNN-based model to predict the popularity of a petition based on its textual content and use it to model the influence of other petition signers. |
| Outcome: | The proposed model is based on UK and US government petition datasets and is compared with previous work on predicting popularity over time based upon initial popularity trajectory. |
Analyzing the Dynamics of Climate Change Discourse on Twitter: A New Annotated Corpus and Multi-Aspect Classification (2024.lrec-main)
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Shuvam Shiwakoti, Surendrabikram Thapa, Kritesh Rauniyar, Akshyat Shah, Aashish Bhandari, Usman Naseem
| Challenge: | a lack of data on climate change discourse has highlighted the need for further advancement . a new study examines the discourse on social media platforms that ignores climate change . |
| Approach: | They analyze climate change discourse on Twitter using a meticulously annotated dataset . they find relevance, stance, hate speech, direction of hate, humor and humor are key aspects . |
| Outcome: | The proposed method combines annotated tweets with a dataset of 15,309 tweets . it reveals tweet distribution patterns, stance prevalence, and hate speech trends . |
Beyond Binary: Towards Embracing Complexities in Cyberbullying Detection and Intervention - a Position Paper (2024.lrec-main)
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Kanishk Verma, Kolawole John Adebayo, Joachim Wagner, Megan Reynolds, Rebecca Umbach, Tijana Milosevic, Brian Davis
| Challenge: | Existing methods for CB detection oversimplify the problem of CB as a binary classification task. |
| Approach: | They propose to use large language models to generate CB-related datasets . they propose to combine cognitive and linguistic models to help identify CB incidents . |
| Outcome: | The proposed approach aims to help researchers and policymakers make informed decisions . it uses large language models such as Claude-2 and Llama2-Chat to generate CB-related datasets . |
ArCovidVac: Analyzing Arabic Tweets About COVID-19 Vaccination (2022.lrec-1)
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| Challenge: | Social media are integrated with our daily life and are used to circulate information. |
| Approach: | They develop and publicly release the first largest manually annotated Arabic tweet dataset for COVID-19 vaccination campaign. |
| Outcome: | The proposed dataset is the largest manually annotated Arabic tweet dataset for COVID-19 vaccination campaign, covering many countries in the Arab region. |
Privacy by Design and Language Resources (2020.lrec-1)
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| Challenge: | Privacy by Design is an approach in which privacy and data protection are embedded throughout the project lifecycle . the principle of Privacy by design was first mentioned in the 1995 EU Data Protection Directive . |
| Approach: | a paper proposes to analyze the practical meaning of Privacy by Design in the context of Language Resources . the paper propose measures and safeguards that can be implemented by the community to ensure respect of this principle. |
| Outcome: | The proposed paper analyzes the practical meaning of Privacy by Design in the context of Language Resources . proposed safeguards can be implemented by the community to ensure respect of this principle. |
GPT Deciphering Fedspeak: Quantifying Dissent Among Hawks and Doves (2023.findings-emnlp)
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| Challenge: | We use GPT-4 to quantify dissent among members on the topic of inflation . transcripts and minutes reflect the diversity of member views in a way that is lost or omitted from the public statements. |
| Approach: | They use transcripts and minutes to quantify dissent among FOMC members . they find that transcripts reflect diversity of member views in a way that is lost or omitted . |
| Outcome: | The proposed method better captures extremes, which mirror human annotations, and suggests that Large Language Models can avoid noise in this nuanced context. |
The TalkMoves Dataset: K-12 Mathematics Lesson Transcripts Annotated for Teacher and Student Discursive Moves (2022.lrec-1)
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| Challenge: | Currently, classroom recordings are limited due to practical and privacy concerns and sharing is restricted due to limited access to valuable resources and data sets. |
| Approach: | They propose to use the TalkMoves dataset to analyze the nature of teacher and student discourse in K-12 math classrooms. |
| Outcome: | The TalkMoves dataset contains 567 human-annotated K-12 mathematics lesson transcripts derived from video recordings. |
Examining Temporalities on Stance Detection towards COVID-19 Vaccination (2024.lrec-main)
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| Challenge: | Existing studies have highlighted the importance of vaccination as an effective strategy to control the transmission of the COVID-19 virus. |
| Approach: | They evaluate a range of transformer-based models using chronological and random splits of social media data to examine the impact of temporal concept drift on stance detection towards COVID-19 vaccination. |
| Outcome: | The proposed models show that the models performed better with chronological and random splits than with random split models. |
From Laughter to Inequality: Annotated Dataset for Misogyny Detection in Tamil and Malayalam Memes (2024.lrec-main)
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Rahul Ponnusamy, Kathiravan Pannerselvam, Saranya R, Prasanna Kumar Kumaresan, Sajeetha Thavareesan, Bhuvaneswari S, Anshid K.a, Susminu S Kumar, Paul Buitelaar, Bharathi Raja Chakravarthi
| Challenge: | a new form of memes has emerged to combat misogyny and harmful stereotypes . authors present a dataset to analyze online misogamy in Tamil and Malayalam communities . |
| Approach: | They propose to create an annotated dataset with detailed annotation guidelines to analyze online misogyny within Tamil and Malayalam-speaking communities. |
| Outcome: | The proposed dataset reveals the world of gender bias and stereotypes in Tamil and Malayalam-speaking communities. |
Jailbreak-Tuning: Models Efficiently Learn Jailbreak Susceptibility (2025.emnlp-main)
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Brendan Murphy, Dillon Bowen, Shahrad Mohammadzadeh, Tom Tseng, Julius Broomfield, Adam Gleave, Kellin Pelrine
| Challenge: | a recent study shows that fine-tuning can produce helpful-only models with safeguards destroyed. |
| Approach: | They propose a method for fine-tuning models to generate detailed, high-quality responses to harmful requests. |
| Outcome: | The proposed method produces helpful-only models with safeguards destroyed . OpenAI, Google, and Anthropic models will fully comply with requests for CBRN assistance . |
Argument-based Detection and Classification of Fallacies in Political Debates (2023.emnlp-main)
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| Challenge: | Fallacies are arguments that employ faulty reasoning, causing inaccurate conclusions and invalid inferences . ad hominem fallacy is one of the most common fallacy labels used in political debates despite its use in many scenarios . |
| Approach: | They extend the ElecDeb60To16 dataset of U.S. presidential debates annotated with fallacious arguments by incorporating the most recent Trump-Biden debate. |
| Outcome: | The proposed method extends the ElecDeb60To16 dataset of U.S. presidential debates annotated with fallacious arguments . |
Foveate, Attribute, and Rationalize: Towards Physically Safe and Trustworthy AI (2023.findings-acl)
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| Challenge: | Covertly unsafe text is an area of particular interest as it is difficult to detect as harmful . previous work focused on explicit violent text and typically expressed through violent keywords. |
| Approach: | They propose a framework that leverages external knowledge for trustworthy rationale generation in the context of safety. |
| Outcome: | The proposed framework improves safety classification accuracy by 5.9% on the SafeText dataset, and shows that it is more accurate than previous frameworks. |
ArMeme: Propagandistic Content in Arabic Memes (2024.emnlp-main)
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| Challenge: | a lack of media literacy is a major factor contributing to the spread of misleading information on social media. |
| Approach: | They analyze a dataset of 6K Arabic memes with manual annotations . they propose to develop computational tools for their detection . |
| Outcome: | The proposed dataset is a first resource for Arabic multimodal research. |