ResearchTrend.AI
A Graph-to-Text Approach to Knowledge-Grounded Response Generation in Human-Robot Interaction

A Graph-to-Text Approach to Knowledge-Grounded Response Generation in Human-Robot Interaction

Nicholas Walker
Stefan Ultes
Pierre Lison
ArXivPDFHTML

Papers citing "A Graph-to-Text Approach to Knowledge-Grounded Response Generation in Human-Robot Interaction"

4 / 4 papers shown
Title
Retrieval-Augmented Neural Response Generation Using Logical Reasoning and Relevance Scoring
Retrieval-Augmented Neural Response Generation Using Logical Reasoning and Relevance Scoring
Nicholas Walker
Stefan Ultes
Pierre Lison
RALM
LRM
8
1
0
20 Oct 2023
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Sébastien Bubeck
Varun Chandrasekaran
Ronen Eldan
J. Gehrke
Eric Horvitz
...
Scott M. Lundberg
Harsha Nori
Hamid Palangi
Marco Tulio Ribeiro
Yi Zhang
ELM
AI4MH
AI4CE
ALM
197
2,953
0
22 Mar 2023
LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action
LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action
Dhruv Shah
B. Osinski
Brian Ichter
Sergey Levine
LM&Ro
136
430
0
10 Jul 2022
Task-Oriented Dialogue as Dataflow Synthesis
Task-Oriented Dialogue as Dataflow Synthesis
Semantic Machines
Jacob Andreas
J. Bufe
David Burkett
Charles C. Chen
...
Izabela Witoszko
Jason Wolfe
A. Wray
Yuchen Zhang
Alexander Zotov
AIFin
180
151
0
24 Sep 2020