Priberam

Author Archives: admin

From Captions to Natural Language Explanations

The growing importance of the Explainable Artificial Intelligence (XAI) field has resulted in the proposal of several methods for producing visual heatmaps of the classification decisions of deep learning models. However, visual explanations are not enough since different end-users have … Read More

Revealing semantic and emotional structure of suicide notes

Understanding how people who commit suicide perceive their cognitive states and emotions represents a crucially open scientific challenge. We build upon cognitive network science, psycholinguistics, and semantic frame theory to introduce a network representation of suicidal ideation as expressed in … Read More

NLP at Cleverly and Multilingual Email Zoning

Cleverly is an end-to-end AI layer for customer service platforms that provides intelligent automation and efficiency and unlike others is easy to use. We reduce the effort agents spend on repetitive tasks and searching for the right information, giving them … Read More

Fact-checking as a conversation

Misinformation is considered one of the major challenges of our times resulting in numerous efforts against it. Fact-checking, the task of assessing whether a claim is true or false, is considered a key weapon in reducing its impact. In the … Read More

Visual Attention with Sparse and Continuous Transformations

Visual attention mechanisms have become an important component of neural network models for Computer Vision applications, allowing them to attend to finite sets of objects or regions and identify relevant features. A key component of attention mechanisms is the differentiable … Read More

Explainability for Sequential Decision-Making

Machine learning has been used to aid decision-making in several domains, from healthcare to finance. Understanding the decision process of ML models is paramount in high-stakes decisions that impact people’s lives, otherwise, loss of control and lack of trust may … Read More

A brief history of Spoken Language Understanding

Spoken Language Understanding consists in extracting semantic information conveyed by speech signal in order to project it into a representation manageable by a software application. This research topic encompasses several tasks like domain classification, named entity recognition, slot filling… By … Read More

TrimTuner: Efficient Optimization of Machine Learning Jobs in the Cloud via Sub-Sampling

This work introduces TrimTuner – the first system for optimizing machine learning jobs in the cloud by exploiting sub-sampling techniques to reduce the cost of the optimization process, while keeping into account user-specified constraints. TrimTuner jointly optimizes the cloud and … Read More

Preference Modeling with Context-Dependent Salient Features

This talk considers the preference modeling problem and addresses the fact that pairwise comparison data often reflects irrational choice, e.g. intransitivity. Our key observation is that two items compared in isolation from other items may be compared based on only … Read More

The Explanation Game: Towards Prediction Explainability through Sparse Communication

Explainability is a topic of growing importance in NLP. In this work, we provide a unified perspective of explainability as a communication problem between an explainer and a layperson about a classifier’s decision. We use this framework to compare several … Read More