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Truth Social, launched as a social media platform with a focus on free speech, has become a prominent space for political discourse, attracting a user base with diverse, yet often conservative, viewpoints. As an emerging platform with…

Controversy is a reflection of our zeitgeist, and an important aspect to any discourse. The rise of large language models (LLMs) as conversational systems has increased public reliance on these systems for answers to their various…

We use instruction-tuned Large Language Models (LLMs) like GPT-4, Llama 3, MiXtral, or Aya to position political texts within policy and ideological spaces. We ask an LLM where a tweet or a sentence of a political text stands on the focal…

Many governments impose traditional censorship methods on social media platforms. Instead of removing it completely, many social media companies, including Twitter, only withhold the content from the requesting country. This makes such…

We present QuAC, a dataset for Question Answering in Context that contains 14K information-seeking QA dialogs (100K questions in total). The dialogs involve two crowd workers: (1) a student who poses a sequence of freeform questions to…

Although most people support climate action, widespread underestimation of others' support stalls individual and systemic changes. In this preregistered experiment, we test whether large language models (LLMs) can reliably predict these…

The accessibility of legal information remains a constant challenge, particularly for laypersons seeking to understand and apply complex institutional texts. While the European Union provides open access to legislation, parliamentary…

This paper systematically examines nation-level biases exhibited by Large Language Models (LLMs) within the domain of International Relations (IR). Leveraging historical records from the United Nations Security Council (UNSC), we developed…

Political speeches and debates play an important role in shaping the images of politicians, and the public often relies on media outlets to select bits of political communication from a large pool of utterances. It is an important research…

The patterns in which the syntax of different languages converges and diverges are often used to inform work on cross-lingual transfer. Nevertheless, little empirical work has been done on quantifying the prevalence of different syntactic…

Large language models (LLMs) may not equitably represent diverse global perspectives on societal issues. In this paper, we develop a quantitative framework to evaluate whose opinions model-generated responses are more similar to. We first…

Toxic and uncivil politics is widely seen as a growing threat to democratic values and governance, yet our understanding of the drivers and evolution of political incivility remains limited. Leveraging a novel dataset of nearly 18 million…

During the past decade, several areas of speech and language understanding have witnessed substantial breakthroughs from the use of data-driven models. In the area of dialogue systems, the trend is less obvious, and most practical systems…

Traditional dialogue summarization primarily focuses on dialogue content, assuming it comprises adequate information for a clear summary. However, this assumption often fails for discussions grounded in shared background, where participants…

Parliamentary transcripts provide a valuable resource to understand the reality and know about the most important facts that occur over time in our societies. Furthermore, the political debates captured in these transcripts facilitate…

In this contribution, we propose to analyze the statements coming from two ''civic tech'' platforms-the governmental platform, ''Grand D{\'e}bat National'' and, its political and algorithmic response proposed by a Yellow Vest collective,…

This paper presents a dataset collected from natural dialogs which enables to test the ability of dialog systems to learn new facts from user utterances throughout the dialog. This interactive learning will help with one of the most…

This paper addresses decision-aiding problems that involve multiple objectives and uncertain states of the world. Inspired by the capability approach, we focus on cases where a policy maker chooses an act that, combined with a state of the…

This paper introduces the Material Contracts Corpus (MCC), a publicly available dataset comprising over one million contracts filed by public companies with the U.S. Securities and Exchange Commission (SEC) between 2000 and 2023. The MCC…

Discovering the existence of universal adversarial perturbations had large theoretical and practical impacts on the field of adversarial learning. In the text domain, most universal studies focused on adversarial prefixes which are added to…