ILLC News & Events

This position is part of the EC-funded project Global Under-Resourced Media Translation (GoURMeT). The overall aim of the project is to develop data-efficient NMT by exploiting prior linguistic knowledge within deep generative models. A central theme of the project is latent variable modelling and for that experience with approximate inference and efficient gradient estimation for deep generative models is a must. The successful applicant will work under the supervision of Dr Wilker Aziz and in collaboration with a PhD candidate (already funded by GoURMet).

This position is part of the Distributed dynamic REpresentations for diAlogue Management (DREAM) Project, which is funded by an ERC Consolidator Grant and will eventually employ two PhD candidates and two postdoctoral researchers.

The aim of the DREAM Project is to establish new computational models for dialogue agents that can learn from data about language use, integrating linguistic and perceptual information and leading to more human-like and effective communication. These models will be grounded in linguistic theories of dialogue, but exploit recent advances in artificial neural networks that will allow them to learn the representations that they manipulate directly from experience. Model analysis and interpretation are key aspects of the project.

The ILLC has a new group, called the Causal Inference Lab, dedicated to investigating causality. The group hosts a reading group every second Monday, 13:00-15:00, which everyone very welcome to attend.

For our next session, Monday 18 February 13:00-15:00, we will read Rachael Briggs' paper, 'Interventionist Counterfactuals' (https://doi.org/10.1007/s11098-012-9908-5). Briggs applies causal models to represent the truth-conditionals of counterfactuals such as "If you had taken the train or the metro, you would have arrived on time."

If you are interested in discussing causal inference with us, please do come along!

We interact with computers every day, and often using something like human language. There is therefore a huge amount of research going into how to represent human language computationally. Modelling words as vectors has been one of the most successful approaches over recent years. However, it is not immediately clear how to combine word vectors together to make phrases and sentences. On the other hand, formal semantics gives a clear
account of how to compose words, but it is not so obvious how to represent their meanings. I will give an overview of the model I work with that shows how to combine word vectors using formal semantics. I will also describe its limitations and will appreciate ideas and questions.

Abstract:
In contemporary Western philosophy, destruction or deconstruction of metaphysics has been presented by prominent thinkers like Levinas, Derrida or Schürmann as the liberation of an an-archic way of thinking. The possibility of questioning and acting beyond the «arkhè», beyond the principle (commandment and beginning at the same time), has opened new perspectives in ontology and ethics. Levinas, for example, characterizes the relation to the Other in terms of «an-archic responsibility». Interestingly, such an ontological and ethical anarchy has always been strictly distinguished from political anarchism. Can we envisage a confrontation between the two traditions? Is "post anarchism" a satisfactory way of setting it up?