Work

Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches

Year: 2023

Type: conference-paper

Abstract: People rely heavily on context to enrich meaning beyond what is literally said, enabling concise but effective communication.To interact successfully and naturally with people, LLMs and other user-facing NLP systems will require similar skills in pragmatics: relying on various types of context-from shared linguistic goals and conventions, to the visual and embodied world-to use language effectively.We survey existing grounded settings and pragmatic modeling approaches and analyze how the task goals, environmental contexts, and communicative affordances in each work enrich linguistic meaning.We present recommendations for future grounded task design to naturally elicit pragmatic phenomena, and suggest directions that focus on a broader range of communicative contexts and affordances.

DOI: 10.18653/v1/2023.findings-emnlp.840

Authors: Daniel Fried, Nicholas Tomlin, Jennifer Hu, Roma Patel, Aida Nematzadeh

Institutions: Carnegie Mellon University, University of California, Berkeley, Brown University, Massachusetts Institute of Technology, Google DeepMind (United Kingdom)

Language: English

Topic: Speech and dialogue systems

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Funders: National Science Foundation, Defense Advanced Research Projects Agency

OpenAlex ID: W4389524592

FWCI: 1.972

Cites: 195

Cited by: 11

Related to: 10