3 citations · 9 across the 5 of their papers we have counts for
7 papers
AI-Augmented Predictions: LLM Assistants Improve Human Forecasting Accuracy
Philipp Schoenegger, Peter S. Park, Ezra Karger +2
Large language models (LLMs) match and sometimes exceeding human performance in many domains. This study explores the potential of LLMs to augment human judgement in a forecasting…
Do Large Language Models know what humans know?
Sean Trott, Cameron Jones, Tyler Chang +2
Humans can attribute beliefs to others. However, it is unknown to what extent this ability results from an innate biological endowment or from experience accrued through child deve…
Contextualized Sensorimotor Norms: multi-dimensional measures of sensorimotor strength for ambiguous English words, in context
Sean Trott, Benjamin Bergen
Most large language models are trained on linguistic input alone, yet humans appear to ground their understanding of words in sensorimotor experience. A natural solution is to augm…
RAW-C: Relatedness of Ambiguous Words--in Context (A New Lexical Resource for English)
Sean Trott, Benjamin Bergen
Most words are ambiguous--i.e., they convey distinct meanings in different contexts--and even the meanings of unambiguous words are context-dependent. Both phenomena present a chal…
(Re)construing Meaning in NLP
Sean Trott, Tiago Timponi Torrent, Nancy Chang +1
Human speakers have an extensive toolkit of ways to express themselves. In this paper, we engage with an idea largely absent from discussions of meaning in natural language underst…
Processing Natural Language About Ongoing Actions
Steve Doubleday, Sean Trott, Jerome Feldman
Actions may not proceed as planned; they may be interrupted, resumed or overridden. This is a challenge to handle in a natural language understanding system. We describe extensions…
Exploiting Deep Semantics and Compositionality of Natural Language for Human-Robot-Interaction
Manfred Eppe, Sean Trott, Jerome Feldman
We develop a natural language interface for human robot interaction that implements reasoning about deep semantics in natural language. To realize the required deep analysis, we em…