1 citations · 3 across the 15 of their papers we have counts for
15 papers
Fine PT-PT Web: A High-Quality 41 Billion Tokens Data Collection of the European Portuguese Web
Gonçalo Vinagre, Rui Pedro Guerra, Pedro Gomes +7
Curating Web corpora for regional language variants like European Portuguese (PT-PT) is heavily bottlenecked by dialectal overlap (mainly with PT-BR) and data processing scale. Thi…
Large-Scale User Behavior Analysis in Multimodal AI-Assisted Manual Task Execution
Rafael Ferreira, Diogo Tavares, Diogo Glória-Silva +2
Conversational Task Assistants (CTAs) are multimodal dialogue systems that support users in complex real-world tasks such as cooking and DIY through voice, text, image, and video i…
AMALIA-VL: A Native European Portuguese Open-Source Vision and Language Model
Diogo Glória-Silva, João Cardeira, Manuel Letras da Luz +8
Large Vision and Language Models (LVLMs) have advanced rapidly, yet European Portuguese (pt-PT) remains systematically underserved by existing open-source multimodal models, which…
PorTEXTO: A European Portuguese Benchmark for Visual Text Extraction
João Cardeira, Diogo Glória-Silva, Manuel Letras da Luz +4
European Portuguese (pt-PT) is largely absent from Optical Character Recognition (OCR) benchmarks, which skew toward high-resource languages. The few benchmarks that cover pt-PT fo…
RedTWIZ: Diverse LLM Red Teaming via Adaptive Attack Planning
Artur Horal, Daniel Pina, Henrique Paz +7
This paper presents the vision, scientific contributions, and technical details of RedTWIZ: an adaptive and diverse multi-turn red teaming framework, to audit the robustness of Lar…
Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures
Tyler A. Chang, Catherine Arnett, Abdelrahman Sadallah +377
To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and cultures. In this paper, we pre…
Multi-trait User Simulation with Adaptive Decoding for Conversational Task Assistants
Rafael Ferreira, David Semedo, João Magalhães
Conversational systems must be robust to user interactions that naturally exhibit diverse conversational traits. Capturing and simulating these diverse traits coherently and effici…
Show and Guide: Instructional-Plan Grounded Vision and Language Model
Diogo Glória-Silva, David Semedo, João Magalhães
Guiding users through complex procedural plans is an inherently multimodal task in which having visually illustrated plan steps is crucial to deliver an effective plan guidance. Ho…
GlórIA -- A Generative and Open Large Language Model for Portuguese
Ricardo Lopes, João Magalhães, David Semedo
Significant strides have been made in natural language tasks, largely attributed to the emergence of powerful large language models (LLMs). These models, pre-trained on extensive a…
Plan-Grounded Large Language Models for Dual Goal Conversational Settings
Diogo Glória-Silva, Rafael Ferreira, Diogo Tavares +2
Training Large Language Models (LLMs) to follow user instructions has been shown to supply the LLM with ample capacity to converse fluently while being aligned with humans. Yet, it…
TWIZ-v2: The Wizard of Multimodal Conversational-Stimulus
Rafael Ferreira, Diogo Tavares, Diogo Silva +6
In this report, we describe the vision, challenges, and scientific contributions of the Task Wizard team, TWIZ, in the Alexa Prize TaskBot Challenge 2022. Our vision, is to build T…
Rating Prediction in Conversational Task Assistants with Behavioral and Conversational-Flow Features
Rafael Ferreira, David Semedo, João Magalhães
Predicting the success of Conversational Task Assistants (CTA) can be critical to understand user behavior and act accordingly. In this paper, we propose TB-Rater, a Transformer mo…
The Wizard of Curiosities: Enriching Dialogues with Fun Facts
Frederico Vicente, Rafael Ferreira, David Semedo +1
Introducing curiosities in a conversation is a way to teach something new to the person in a pleasant and enjoyable way. Enriching dialogues with contextualized curiosities can imp…
Grounded Complex Task Segmentation for Conversational Assistants
Rafael Ferreira, David Semedo, João Magalhães
Following complex instructions in conversational assistants can be quite daunting due to the shorter attention and memory spans when compared to reading the same instructions. Henc…
Task Conditioned BERT for Joint Intent Detection and Slot-filling
Diogo Tavares, Pedro Azevedo, David Semedo +2
Dialogue systems need to deal with the unpredictability of user intents to track dialogue state and the heterogeneity of slots to understand user preferences. In this paper we inve…