Search Results for author: Felix Gervits

Found 15 papers, 5 papers with code

A System For Robot Concept Learning Through Situated Dialogue

no code implementations SIGDIAL (ACL) 2022 Benjamin Kane, Felix Gervits, Matthias Scheutz, Matthew Marge

We evaluate the system by comparing learning efficiency to a human baseline in a collaborative reference resolution task and show that the system is effective and efficient in learning new concepts, and that it can informatively generate explanations about its behavior.

One-Shot Learning Question Generation +1

DriVLMe: Enhancing LLM-based Autonomous Driving Agents with Embodied and Social Experiences

1 code implementation5 Jun 2024 Yidong Huang, Jacob Sansom, Ziqiao Ma, Felix Gervits, Joyce Chai

Recent advancements in foundation models (FMs) have unlocked new prospects in autonomous driving, yet the experimental settings of these studies are preliminary, over-simplified, and fail to capture the complexity of real-world driving scenarios in human environments.

Autonomous Driving Language Modeling +3

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

1 code implementation22 Oct 2022 Ziqiao Ma, Ben VanDerPloeg, Cristian-Paul Bara, Huang Yidong, Eui-In Kim, Felix Gervits, Matthew Marge, Joyce Chai

To this end, we introduce Dialogue On the ROad To Handle Irregular Events (DOROTHIE), a novel interactive simulation platform that enables the creation of unexpected situations on the fly to support empirical studies on situated communication with autonomous driving agents.

Autonomous Driving Dialogue Act Classification +2

How Should Agents Ask Questions For Situated Learning? An Annotated Dialogue Corpus

1 code implementation SIGDIAL (ACL) 2021 Felix Gervits, Antonio Roque, Gordon Briggs, Matthias Scheutz, Matthew Marge

Intelligent agents that are confronted with novel concepts in situated environments will need to ask their human teammates questions to learn about the physical world.

Novel Concepts Question Generation +1

Disfluent but effective? A quantitative study of disfluencies and conversational moves in team discourse

no code implementations COLING 2016 Felix Gervits, Kathleen Eberhard, Matthias Scheutz

The purpose of this paper is to address those gaps in the following ways: (1) investigate which properties of task-oriented discourse correspond with effective performance in human teams, and (2) discuss how and to what extent these properties can be utilized in spoken dialogue systems.

Decision Making Spoken Dialogue Systems

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