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20222026
most citedUsing Large Language Models for Zero-Shot Natural Language Generation from Knowledge Graphs

6 citations · 19 across the 22 of their papers we have counts for

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5 papers · 1 filter

cs.CL2025

Investigating the Representation of Backchannels and Fillers in Fine-tuned Language Models

Yu Wang, Leyi Lao, Langchu Huang +3

Backchannels and fillers are important linguistic expressions in dialogue, but often treated as 'noise' to be bypassed in modern transformer-based language models (LMs). Here, we s…

cs.RO2025

Into the Wild: When Robots Are Not Welcome

Shaul Ashkenazi, Gabriel Skantze, Jane Stuart-Smith +1

Social robots are increasingly being deployed in public spaces, where they face not only technological difficulties and unexpected user utterances, but also objections from stakeho…

cs.CL2025

Detecting Referring Expressions in Visually Grounded Dialogue with Autoregressive Language Models

Bram Willemsen, Gabriel Skantze

In this paper, we explore the use of a text-only, autoregressive language modeling approach for the extraction of referring expressions from visually grounded dialogue. More specif…

eess.AS2025

"Dyadosyncrasy", Idiosyncrasy and Demographic Factors in Turn-Taking

Julio Cesar Cavalcanti, Gabriel Skantze

Turn-taking in dialogue follows universal constraints but also varies significantly. This study examines how demographic (sex, age, education) and individual factors shape turn-tak…

cs.CL2025

Representation of perceived prosodic similarity of conversational feedback

Livia Qian, Carol Figueroa, Gabriel Skantze

Vocal feedback (e.g., `mhm', `yeah', `okay') is an important component of spoken dialogue and is crucial to ensuring common ground in conversational systems. The exact meaning of s…