activity
20232026
most citedJoint Learning of Context and Feedback Embeddings in Spoken Dialogue

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Do Factual Recall Mechanisms Carry over from Text to Speech in Multimodal Language Models?

Luca Modica, Filip Landin, Mehrdad Farahani +3

In recent years, several Speech Language Models (SLMs) that represent speech and written text jointly have been presented. The question then emerges about how model-internal mechan…

cs.CL2026

Aligning Backchannel and Dialogue Context Representations via Contrastive LLM Fine-Tuning

Livia Qian, Gabriel Skantze

Backchannels (e.g., `yeah', `mhm', and `right') are short, non-interruptive feedback signals whose lexical form and prosody jointly convey pragmatic meaning. While prior computatio…

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…

cs.CL20241 cited

Joint Learning of Context and Feedback Embeddings in Spoken Dialogue

Livia Qian, Gabriel Skantze

Short feedback responses, such as backchannels, play an important role in spoken dialogue. So far, most of the modeling of feedback responses has focused on their timing, often neg…

cs.CL2023

Resolving References in Visually-Grounded Dialogue via Text Generation

Bram Willemsen, Livia Qian, Gabriel Skantze

Vision-language models (VLMs) have shown to be effective at image retrieval based on simple text queries, but text-image retrieval based on conversational input remains a challenge…