9 citations · 29 across the 20 of their papers we have counts for
23 papers
Does CoT-Pass@k Really Check the CoT? A Multilingual Mathematical Audit
Tarık Tuna Taşaltı, Burcu Hüdaverdi, David Semedo
Pass@k measures whether a model reaches a correct answer under repeated sampling, but never how: a lucky guess counts the same as sound reasoning. CoT-Pass@k was proposed to close…
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…
ALBA: A European Portuguese Benchmark for Evaluating Language and Linguistic Dimensions in Generative LLMs
Inês Vieira, Inês Calvo, Iago Paulo +6
As Large Language Models (LLMs) expand across multilingual domains, evaluating their performance in under-represented languages becomes increasingly important. European Portuguese…
AMALIA Technical Report: A Fully Open Source Large Language Model for European Portuguese
Afonso Simplício, Gonçalo Vinagre, Miguel Moura Ramos +19
Despite rapid progress in open large language models (LLMs), European Portuguese (pt-PT) remains underrepresented in both training data and native evaluation, with machine-translat…
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…
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…
Assisting News Media Editors with Cohesive Visual Storylines
Gonçalo Marcelino, David Semedo, André Mourão +3
Creating a cohesive, high-quality, relevant, media story is a challenge that news media editors face on a daily basis. This challenge is aggravated by the flood of highly relevant…
Knowledge-driven Answer Generation for Conversational Search
Mariana Leite, Rafael Ferreira, David Semedo +1
The conversational search paradigm introduces a step change over the traditional search paradigm by allowing users to interact with search agents in a multi-turn and natural fashio…
BERT Embeddings Can Track Context in Conversational Search
Rafael Ferreira, David Semedo, Joao Magalhaes
The use of conversational assistants to search for information is becoming increasingly more popular among the general public, pushing the research towards more advanced and sophis…
Open-Domain Conversational Search Assistant with Transformers
Rafael Ferreira, Mariana Leite, David Semedo +1
Open-domain conversational search assistants aim at answering user questions about open topics in a conversational manner. In this paper we show how the Transformer architecture ac…
Cross-Modal Subspace Learning with Scheduled Adaptive Margin Constraints
David Semedo, João Magalhães
Cross-modal embeddings, between textual and visual modalities, aim to organise multimodal instances by their semantic correlations. State-of-the-art approaches use maximum-margin m…
Diachronic Cross-modal Embeddings
David Semedo, João Magalhães
Understanding the semantic shifts of multimodal information is only possible with models that capture cross-modal interactions over time. Under this paradigm, a new embedding is ne…
A Benchmark of Visual Storytelling in Social Media
Gonçalo Marcelino, David Semedo, André Mourão +3
Media editors in the newsroom are constantly pressed to provide a "like-being there" coverage of live events. Social media provides a disorganised collection of images and videos t…
Temporal Cross-Media Retrieval with Soft-Smoothing
David Semedo, João Magalhães
Multimedia information have strong temporal correlations that shape the way modalities co-occur over time. In this paper we study the dynamic nature of multimedia and social-media…
Inferring User Gender from User Generated Visual Content on a Deep Semantic Space
David Semedo, João Magalhães, Flávio Martins
In this paper we address the task of gender classification on picture sharing social media networks such as Instagram and Flickr. We aim to infer the gender of an user given only a…