Related papers: Project Debater APIs: Decomposing the AI Grand Cha…
Since its inception in 2016, the Alexa Prize program has enabled hundreds of university students to explore and compete to develop conversational agents through the SocialBot Grand Challenge. The goal of the challenge is to build agents…
Dialogue-based human-AI collaboration can revolutionize collaborative problem-solving, creative exploration, and social support. To realize this goal, the development of automated agents proficient in skills such as negotiating, following…
Can artificial intelligence discover, from raw experience and without human supervision, concepts that humans have discovered? One challenge is that human concepts themselves are fluid: conceptual boundaries can shift, split, and merge as…
We argue that enabling human-AI dialogue, purposed to support joint reasoning (i.e., 'inquiry'), is important for ensuring that AI decision making is aligned with human values and preferences. In particular, we point to logic-based models…
We present a novel framework designed to extend model reconciliation approaches, commonly used in human-aware planning, for enhanced human-AI interaction. By adopting a structured argumentation-based dialogue paradigm, our framework enables…
While there is an increased discourse on large language models (LLMs) like ChatGPT and DeepSeek, there is no comprehensive understanding of how users of online platforms, like Reddit, perceive these models. This is an important omission…
Asynchronous online discussions enable diverse participants to co-construct knowledge beyond individual contributions. This process ideally evolves through sequential phases, from superficial information exchange to deeper synthesis.…
A system that could reliably identify and sum up the most important points of a conversation would be valuable in a wide variety of real-world contexts, from business meetings to medical consultations to customer service calls. Recent…
Since the first AI-HRI held at the 2014 AAAI Fall Symposium Series, a lot of the presented research and discussions have emphasized how artificial intelligence (AI) developments can benefit human-robot interaction (HRI). This portrays HRI…
Online forums provide a unique opportunity for online users to share comments and exchange information on a particular topic. Understanding user behaviour is valuable to organizations and has applications for social and security strategies,…
Computational argumentation offers formal frameworks for transparent, verifiable reasoning but has traditionally been limited by its reliance on domain-specific information and extensive feature engineering. In contrast, LLMs excel at…
The increasing sophistication of large language models (LLMs) has sparked growing concerns regarding their potential role in exacerbating ideological polarization through the automated generation of persuasive and biased content. This study…
To make AI systems broadly useful for challenging real-world tasks, we need them to learn complex human goals and preferences. One approach to specifying complex goals asks humans to judge during training which agent behaviors are safe and…
This paper investigates the potential of AI models, particularly large language models (LLMs), to support knowledge exploration and augment human creativity during ideation. We present "Latent Lab" an interactive tool for discovering…
The paper presents an approach to build a question and answer system that is capable of processing the information in a large dataset and allows the user to gain knowledge from this dataset by asking questions in natural language form. Key…
Recent dense retrievers increasingly leverage the robust text understanding capabilities of Large Language Models (LLMs), encoding queries and documents into a shared embedding space for effective retrieval. However, most existing methods…
Artists occupy a paradoxical position in generative AI: their work trains the models reshaping creative labor. We tested whether their concerns achieve proportional representation in public discourse shaping AI governance. Analyzing public…
A growing body of work has shown that AI-assisted methods -- leveraging large language models, social choice methods, and collective dialogues -- can help navigate polarization and surface common ground in controlled lab settings. But what…
The core premise of AI debate as a scalable oversight technique is that it is harder to lie convincingly than to refute a lie, enabling the judge to identify the correct position. Yet, existing debate experiments have relied on datasets…
Group deliberation enables people to collaborate and solve problems, however, it is understudied due to a lack of resources. To this end, we introduce the first publicly available dataset containing collaborative conversations on solving a…