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Towards Collaborative Plan Acquisition through Theory of Mind Modeling in Situated Dialogue

Collaborative tasks often begin with partial task knowledge and incomplete initial plans from each partner. To complete these tasks, agents need to engage in situated communication with their partners and coordinate their partial plans towards a …

Human Inspired Progressive Alignment and Comparative Learning for Grounded Word Acquisition

Human language acquisition is an efficient, supervised, and continual process. In this work, we took inspiration from how human babies acquire their first language, and developed a computational process for word acquisition through comparative …

In-Context Analogical Reasoning with Pre-Trained Language Models

Analogical reasoning is a fundamental capacity of human cognition that allows us to reason abstractly about novel situations by relating them to past experiences. While it is thought to be essential for robust reasoning in AI systems, conventional …

NLP Reproducibility For All: Understanding Experiences of Beginners

As natural language processing (NLP) has recently seen an unprecedented level of excitement, and more people are eager to enter the field, it is unclear whether current research reproducibility efforts are sufficient for this group of beginners to …

World-to-Words: Grounded Open Vocabulary Acquisition through Fast Mapping in Vision-Language Models

The ability to connect language units to their referents in the physical world, referred to as grounding, is crucial to learning and understanding grounded meanings of words. While humans demonstrate fast mapping in new word learning, it remains …

SEAGULL: An Embodied Agent for Instruction Following through Situated Dialog

The growing demand for advanced AI necessitates the development of an intelligent agent capable of perceiving, reasoning, acting, and communicating within an embodied environment. We introduce SEAGULL, an interactive embodied agent designed for the …

DANLI: Deliberative Agent for Following Natural Language Instructions

Recent years have seen an increasing amount of work on embodied AI agents that can perform tasks by following human language instructions. However, most of these agents are reactive, meaning that they simply learn and imitate behaviors encountered in …

DOROTHIE: Spoken Dialogue for Handling Unexpected Situations in Interactive Autonomous Driving Agents

In the real world, autonomous driving agents navigate in highly dynamic environments full of unexpected situations where pre-trained models are unreliable. In these situations, what is immediately available to vehicles is often only human operators. …

Learning to Mediate Disparities Towards Pragmatic Communication

Human communication is a collaborative process. Speakers, on top of conveying their own intent, adjust the content and language expressions by taking the listeners into account, including their knowledge background, personalities, and physical …

MindCraft: Theory of Mind Modeling for Situated Dialogue in Collaborative Tasks

An ideal integration of autonomous agents in a human world implies that they are able to collaborate on human terms. In particular, theory of mind plays an important role in maintaining common ground during human collaboration and communication. To …