188 citations · 673 across the 20 of their papers we have counts for
23 papers
SYNDICOM: Improving Conversational Commonsense with Error-Injection and Natural Language Feedback
Christopher Richardson, Anirudh Sundar, Larry Heck
Commonsense reasoning is a critical aspect of human communication. Despite recent advances in conversational AI driven by large language models, commonsense reasoning remains a cha…
cTBLS: Augmenting Large Language Models with Conversational Tables
Anirudh S Sundar, Larry Heck
Optimizing accuracy and performance while eliminating hallucinations of open-domain conversational large language models (LLMs) is an open research challenge. A particularly promis…
Commonsense Reasoning for Conversational AI: A Survey of the State of the Art
Christopher Richardson, Larry Heck
Large, transformer-based pretrained language models like BERT, GPT, and T5 have demonstrated a deep understanding of contextual semantics and language syntax. Their success has ena…
Grounding Open-Domain Instructions to Automate Web Support Tasks
Nancy Xu, Sam Masling, Michael Du +4
Grounding natural language instructions on the web to perform previously unseen tasks enables accessibility and automation. We introduce a task and dataset to train AI agents from…
mForms : Multimodal Form-Filling with Question Answering
Larry Heck, Simon Heck, Anirudh Sundar
This paper presents a new approach to form-filling by reformulating the task as multimodal natural language Question Answering (QA). The reformulation is achieved by first translat…
end-to-end training of a large vocabulary end-to-end speech recognition system
Chanwoo Kim, Sungsoo Kim, Kwangyoun Kim +10
In this paper, we present an end-to-end training framework for building state-of-the-art end-to-end speech recognition systems. Our training system utilizes a cluster of Central Pr…