ViPer: Visual Personalization of Generative Models via Individual Preference Learning

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Generative AI technologies are increasingly being incorporated into creativity support tools. However, most generative AI tools rely on text-based prompting, requiring users to translate visual ideas into linguistic descriptions. This approach is misaligne ...

We formalize the problem of prompt compression for large language models (LLMs) and present a framework to unify token-level prompt compression methods which create hard prompts for black-box models. We derive the distortion-rate function for this setup as ...

Text Reuse reveals meaningful reiterations of text in large corpora. Humanities researchers use text reuse to study, e.g., the posterior reception of influential texts or to reveal evolving publication practices of historical media. This research is often ...

Models trained with counterfactually augmented data learn representations of the causal structure of tasks, enabling robust generalization. However, high-quality counterfactual data is scarce for most tasks and not easily generated at scale. When crowdsour ...

Censuses are structured documents of great value for social and demographic history, which became widespread from the nineteenth century on. However, the plurality of formats and the natural variability of historical data make their extraction arduous and ...

In order to provide urban residents with suitable living conditions, it is essential to keep track of the liveability of neighbourhoods. This is traditionally done through surveys and by predictive modelling. However, surveying on a large scale is expensiv ...

Networks are commonly used to represent key processes in biology; examples include transcriptional regulatory networks, protein-protein interaction (PPI) networks, metabolic networks, etc. Databases store many such networks, as graphs, observed or inferred ...

Automatically extracting linear structures from images is a fundamental low-level vision problem with numerous applications in different domains. Centerline detection and radial estimation are the first crucial steps in most Computer Vision pipelines aimin ...

The advent of new technologies in cinema, theatre and virtual reality together with increasing demands for new content, are pushing the boundaries of filmmaking and storytelling to the limits of our imaginations. The potential for 3D film to blur the line ...

Conversational recommenders can help users find their most preferred item among a large range of options, a task that we call preference-based search. ...

ViPer: Visual Personalization of Generative Models via Individual Preference Learning

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SketchAI: A "Sketch-First" Approach to Incorporating Generative AI into Fashion Design

Fundamental Limits of Prompt Compression: A Rate- Distortion Framework for Black-Box Language Models

impresso Text Reuse at Scale. An interface for the exploration of text reuse data in semantically enriched historical newspapers

DISCO: Distilling Counterfactuals with Large Language Models

An end-to-end pipeline for historical censuses processing

Predicting the liveability of Dutch cities with aerial images and semantic intermediate concepts

Models and Algorithms in Biological Network Evolution with Modularity

Multiscale Centerline Extraction Based on Regression and Projection onto the Set of Elongated Structures

Exposure effect on experience and visual perception in stereoscopic visual presentations

Preference-based search with adaptive recommendations