... to the website of the Dialogue Modeling Group in Amsterdam!
We carry out research at the interface of computational linguistics, cognitive modelling and artificial intelligence.
Our aim is to understand how we use language to communicate with each other in situated environments and how dialogue
interaction shapes learning -- about the world and about language itself. These are some of the topics we work on:
Semantics and pragmatics of dialogue phenomena, visually grounded language and visual reasoning,
conversational agents and learning from interaction, language variation and change in communities of speakers.
23/03/2022 We are looking for postdocs to join the group!
2-year project on modelling face-to-face dialogue (gesture and language) using NLP, body-motion analysis, and ML; in collaboration with the Donders Institute. Preferred starting date: 1 July 2022 (vacancy closed - selection underway).
2-year position within the ERC CoG project Distributed Representations for Dialogue Management (DREAM), with considerable freedom on choosing your research agenda. Preferred starting date: 1 September 2022. The vacancy ad and application link will be available soon.
20/03/2022 Arabella J. Sinclair moves out to take up a Lectureship at the University of Aberdeen - congrats, Janie!
14/03/2022 Mario presents his work on strategies of language production at the Language Technology Group Seminar of the Univerisity of Oslo.
15/12/2021 Justine Winkler has joined our team as PhD candidate. Welcome, Justine!
01/10/2021 Joris Baan has joined the group as ELLIS PhD candidate, co-supervised by Barbara Plank. Welcome, Joris!
01/09/2021 Sandro Pezzelle is now Assistant Professor in Responsible AI at the ILLC - congrats, Sandro!
New work by our group to appear at EMNLP, CoNLL, TACL, and SemDial; checkout our publications.
22/02/2021 Blog post by science journalist Iris Proff, featuring work led by Ece on using human gaze to guide image description generation.
Ece will be discussing this work at the AI Meetings of KoƧ University on 9 March.
Lennert Jansen (controlled generation in dialogue)
Gabriele Gennaro (agent adaptation in reference games)
Xinyi Chen (language understanding and reasoning abilities of visually grounded models)
Pauline Sander (meaning change; Erasmus+ student from Saarland)
Jelle Bosscher (interactive language modelling)
Lars Laichter (dialogue style transfer)
Alumni (incomplete list)
Arabella J. Sinclair, postdoc 2019-2022, moved to lecturer (assistant professor) at University of Aberdeen. Marco Del Tredici, PhD candidate 2017-2020, moved to Machine Learning Scientist at Amazon Berlin. Elia Bruni, postdoc 2016-2018, moved to Marie Curie fellow at UPF Barcelona. Ravi Shekhar, PhD candidate 2016-2019, based in Tento and co-supervised with Raffaella Bernardi; moved to postdoc at Queen Mary University of London. Julian J. Schlöder, PhD candiate 2014-2018, moved to postdoc at the ILLC. Janosch Haber, MSc student 2018-2019, moved to PhD candidate at Queen Mary University of London. Laura Aina, MSc student 2015-2017, moved to PhD candidate at UPF Barcelona. Bill Noble, MSc student 2014-2016, moved to PhD candidate at CLASP, University of Gothenburg.
Resources
Datasets, code, and other publicly available resources developed by the Dialogue Modelling Group.
MALeViC: Modeling Adjectives Leveraging Visual Contexts
Dataset of synthetic images with pairs of statements and truth values related to size adjectives, as well as code repository for serveral experiments and analyses that leverage this dataset.
The PhotoBook Dataset: Building Common Ground through Visually Grounded Dialogue
A large-scale collection of 2,500 human-human, visually-grounded and goal-oriented English conversations between pairs of participants. Funded by ParlAI, Facebook AI Research.
The website includes links to download several subsets of the data and to code repositories for several experiments and models.
VISTA: Visually Grounded Talking Agents
Code and overview of research on visually-grounded language in interactive settings presented in a series of papers led jointly with Raffaella Bernardi.
Collective Annotation
Datasets and resources related to the problem of aggregating the judgements of multiple individuals, regarding a linguistic annotation task or similar, into a single collective judgement that reflects the view of the community. Project jointly led with Ulle Endriss.